# api_taskdetail

author: 孙冉;林显军;许士锦;杨智宏;杨双宾;石新发
source: 润滑与密封
site: 维普
title: 基于显微成像与图像识别的在线油液颗粒传感研究
created_at: 2025-09-11 16:23:03.820801
original_link:
  https://www.cqvip.com/doc/journal/3506696376?sign=d9cc97e5a0ea60c1c289159d6f95731881ba3066f81f05407bd8cd2dd7edbb06&expireTime=1789114710544&resourceId=3506696376

summary:
  针对大型充油设备中油液污染颗粒物的动态监测,开发一款基于显微成像与图像识别技术的污染颗粒物视觉传感器,该传感器通过远心物镜、碗状光源以及高速工业相机等器件的配合,实现污染颗粒在油液中运动过程的视频采集。结合图像深度学习技术,根据采集的图像提取污染颗粒物的多维信息特征实现污染颗粒物的计数和分类。通过模拟仿真与理论计算验证光学系统设计的合理性,并使用掩膜板对系统的分辨力进行测试。结果表明,所设计的视觉传感器能实现等效粒径5~200μm的颗粒物检测,能有效识别金属类、纤维类、气泡等不同性质的颗粒物,并对颗粒物的尺寸与等效面积进行计算。该视觉传感器可有效甄别油液中颗粒物形态、性质,提高设备的运行可靠性,防范颗粒物污染造成油液劣化故障率,为大型充油电力设备的故障诊断提供科学工具。

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author: 任一男;彭玉兴;常向东;卢昊
source: 机械设计与制造
site: 维普
title: 钢丝绳横向振动倾斜矩形拟合图像识别研究
created_at: 2025-09-11 16:23:03.821801
original_link:
  https://www.cqvip.com/doc/journal/3506531542?sign=61d10dac582fb03c5088caf9ed4ad068788fc28e9891227ded898453c9b7df0c&expireTime=1789114710544&resourceId=3506531542

summary:
  为了改善传统钢丝绳横向振动图像识别算法的检测效果,提高检测准确率与实时性,降低拍摄中残影现象和背景干扰带来的误差,提出一种基于倾斜矩形拟合的钢丝绳横向振动图像识别算法,并结合Visual Studio编程平台与OpenCV软件库使用C++语言进行算法设计。经过对比验证,在较低的输入图像分辨率(640×480)和帧率(30fps)下,本算法能准确识别钢丝绳横向振动幅值与振动频率,提高了钢丝绳横向振动的检测精度:振幅误差小于0.8%、频率检测误差小于0.15%,降低了由昂贵的高速相机带来的检测成本。

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author: 银宇;闵湘川;杨聪仁;焦芬;韩俊伟;魏茜;黄应;覃文庆
keywords: 智能选矿;预选抛废;深度学习;目标检测;YOLOv8算法
source: 中国有色金属学报
site: 维普
title: 基于YOLOv8的白钨矿石灰度图像识别优化算法
created_at: 2025-09-11 16:23:03.824801
original_link:
  https://www.cqvip.com/doc/journal/3507537961?sign=6f90c67cc3d7a4024c57fe99495d3b8e80d5880d70a2d6525550b08529cc07f1&expireTime=1789114710544&resourceId=3507537961

summary:
  基于X射线透射技术的智能矿石识别算法已在工业生产中实现应用,但由于矿石与废石的物理性质接近,导致X射线透射图像的灰度差异小,且对比度不明显,从而增加了识别的难度。现有算法在精度和速度上仍存在瓶颈需要进一步优化模型性能。为此本研究基于YOLOv8单阶段深度学习算法,提出一种专门针对白钨原矿灰度图像的识别算法YOLOv8-Miner,旨在提高矿石自动化识别的精度和速度。通过对白钨原矿灰度图像数据集的训练和验证,优化了YOLOv8算法的识别性能以满足矿石分选系统对实时性和准确性的双重要求。结果表明:采用图像数据增强、新型损失函数、注意力机制、超参数自动化和轻量化卷积五项技术后,YOLOv8算法在矿石与废石的分类任务中实现了精确且快速的识别,显著降低了计算成本。针对矿石类别的平均精度值(PAP)从0.928增大到0.969,精度值和召回率的调和平均值(F1)从0.85增大到0.87,单张图像纯推理时间仅需2.78 ms,算法参数总量仅为8.33×10。此外本研究还改进了可视化软件以直观展示优化算法在矿石识别中的应用效果,优化后的图像识别算法为白钨矿智能选矿提供了新的技术方案。

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author: Daniel Keysers;Thomas Deselaers;Christian Gollan;Hermann Ney
date: 2007
original_link: https://ieeexplore.ieee.org/document/4250467/
site: ieeeXplore
title: Deformation Models for Image Recognition
created_at: 2025-09-11 16:23:03.825799
summary:
  We present the application of different nonlinear image deformation models to the task of image recognition. The deformation models are especially suited for local changes as they often occur in the presence of image object variability. We show that, among the discussed models, there is one approach that combines simplicity of implementation, low-computational complexity, and highly competitive performance across various real-world image recognition tasks. We show experimentally that the model performs very well for four different handwritten digit recognition tasks and for the classification of medical images, thus showing high generalization capacity. In particular, an error rate of 0.54 percent on the MNIST benchmark is achieved, as well as the lowest reported error rate, specifically 12.6 percent, in the 2005 international ImageCLEF evaluation of medical image specifically categorization.

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author: H. Chang;Y. Yao;A. Koschan;B. Abidi;M. Abidi
date: 2008
original_link: https://ieeexplore.ieee.org/document/4712365/
site: ieeeXplore
title: Spectral range selection for face recognition under various illuminations
created_at: 2025-09-11 16:23:03.827799
summary:
  Multispectral imaging and fusion of multispectral images in visible spectrum have been employed and proved to enhance the recognition performance over conventional broad-band images, especially when the illumination changes. In this paper, we further our study toward the recognition performance of a smaller number of spectral band images. Given the illumination, we propose an automated method that specifies the optimal spectral ranges to achieve an improved recognition performance compared with conventional broad-band images. Our discovery can be practically used for a new customized sensor design associated with given illuminations for an improved face recognition performance over conventional broad-band images.

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author: Ying Wen;Pengfei Shi
date: 2007
original_link: https://ieeexplore.ieee.org/document/4217311/
site: ieeeXplore
title: Image PCA: A New Approach for Face Recognition
created_at: 2025-09-11 16:23:03.829799
summary:
  Two-dimensional principal component analysis (2DPCA) for face recognition has been proposed which is based on 2D matrices. It needs more coefficients for feature vectors than principal component analysis (PCA). In this paper, we develop an idea which is working in the projective feature image obtained by 2DPCA on the original images i.e., image PCA, for efficient face representation and recognition. To test image PCA and evaluate its performance, a number of experiments are performed on two face image database: ORL and Yale face databases. The experimental results show that image PCA achieves the same or even higher recognition rate than 2DPCA, while the former needs less coefficients for feature vectors than the latter.

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author: K. Yogheedha;A.S.A. Nasir;H. Jaafar;S.M. Mamduh
date: 2018
original_link: https://ieeexplore.ieee.org/document/8477639/
site: ieeeXplore
created_at: 2025-09-11 16:23:03.830801
summary:
  A vehicle license plate recognition system is an important proficiency that could be used for identification of engine vehicle all over the earth. It is valuable in numerous applications such as entrance admission, security, parking control, road traffic control, and speed control. However, the system only manages to identify the license number and needs an operator to control the collected data. Therefore, this paper proposes an automatic license plate recognition system by using the image processing and template matching approach. The current study aims to increase the efficiency of license plate recognition system for Universiti Malaysia Perlis (UniMAP) smart university. This venture comprises of simulation program to recognize license plate characters where a captured image of vehicles will be the input. Then, these images will be processed using several image processing techniques and optical character recognition method in order to recognize the segmented number plate. The image processing techniques consist of colour conversion, image segmentation using Otsu's thresholding, noise removal, image subtraction, image cropping and bounding box feature. The optical character recognition based on template matching approach is used to analyse the printed characters on the segmented license plate image and to produce an output data consisting of characters. Overall, the proposed automatic vehicle license plate recognition system is capable to perform the recognition process by successfully recognizing license plate of 13 cars, from a total of 14 cars.

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title:
  Automatic Vehicle License Plate Recognition System Based on Image Processing and Template Matching Approach


author: Yoshihisa Shinagawa
date: 2008
original_link: https://ieeexplore.ieee.org/document/4538227/
site: ieeeXplore
title: Homotopic Image Pseudo-Invariants for Openset Object Recognition and Image Retrieval
created_at: 2025-09-11 16:23:03.831801
summary:
  This paper presents novel homotopic image pseudo-invariants for face recognition based on pixelwise analysis. An exemplar face and test images are matched, and the most similar image is determined first. The homotopic image pseudo-invariants are calculated next to judge whether the most similar image is the same person as the exemplar. The proposed method can be applied to openset recognition. Recognition task can be performed with or without face databases, while the recognition rate is higher when a database is available. This fact facilitates the recognition of faces and various other objects on the Internet. We benchmark the method using FERET as well as the images downloaded from the Internet.

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author: Sinisa Todorovic;Narendra Ahuja
date: 2008
original_link: https://ieeexplore.ieee.org/document/4441718/
site: ieeeXplore
title: Unsupervised Category Modeling, Recognition, and Segmentation in Images
created_at: 2025-09-11 16:23:03.833802
summary:
  Suppose a set of arbitrary (unlabeled) images contains frequent occurrences of 2D objects from an unknown category. This paper is aimed at simultaneously solving the following related problems: (1) unsupervised identification of photometric, geometric, and topological properties of multiscale regions comprising instances of the 2D category; (2) learning a region-based structural model of the category in terms of these properties; and (3) detection, recognition and segmentation of objects from the category in new images. To this end, each image is represented by a tree that captures a multiscale image segmentation. The trees are matched to extract the maximally matching subtrees across the set, which are taken as instances of the target category. The extracted subtrees are then fused into a tree-union that represents the canonical category model. Detection, recognition, and segmentation of objects from the learned category are achieved simultaneously by finding matches of the category model with the segmentation tree of a new image. Experimental validation on benchmark datasets demonstrates the robustness and high accuracy of the learned category models, when only a few training examples are used for learning without any human supervision.

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author: Javier Galbally;Sébastien Marcel;Julian Fierrez
date: 2014
original_link: https://ieeexplore.ieee.org/document/6671991/
site: ieeeXplore
created_at: 2025-09-11 16:23:03.834800
summary:
  To ensure the actual presence of a real legitimate trait in contrast to a fake self-manufactured synthetic or reconstructed sample is a significant problem in biometric authentication, which requires the development of new and efficient protection measures. In this paper, we present a novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts. The objective of the proposed system is to enhance the security of biometric recognition frameworks, by adding liveness assessment in a fast, user-friendly, and non-intrusive manner, through the use of image quality assessment. The proposed approach presents a very low degree of complexity, which makes it suitable for real-time applications, using 25 general image quality features extracted from one image (i.e., the same acquired for authentication purposes) to distinguish between legitimate and impostor samples. The experimental results, obtained on publicly available data sets of fingerprint, iris, and 2D face, show that the proposed method is highly competitive compared with other state-of-the-art approaches and that the analysis of the general image quality of real biometric samples reveals highly valuable information that may be very efficiently used to discriminate them from fake traits.

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title:
  Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition


author: Wenjie Yu;Jing Peng;Jian Li;Yanjie Deng;Hai’an Li
date: 2022
original_link: https://ieeexplore.ieee.org/document/10016132/
site: ieeeXplore
title: Application Research of Image Feature Recognition Algorithm in Visual Image Recognition
created_at: 2025-09-11 16:23:03.835800
summary:
  With the continuous development of computer vision and various advanced imaging equipment, images contain more and more information. The purpose of this paper is to study the application of image feature recognition algorithm in visual image recognition, and propose an image recognition algorithm based on BP fuzzy neural network. The algorithm uses BP fuzzy neural network to perform fusion calculation on the collected images, performs fuzzy operator operations on the fuzzy sets, and then matches the operation results with the database symbols, and performs fuzzy set operations on the two sets of images obtained to obtain the final result. Simulation experiments show that the recognition rate and recognition time of three different algorithms are compared, namely pattern matching method, feature intersection method and neural network. Correct recognition time 12s Regardless of the correct recognition rate or recognition speed, the neural network feature recognition algorithm is better than the other two recognition algorithms.

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author: Harishwaran Hariharan;Andreas Koschan;Besma Abidi;Andrei Gribok;Mongi Abidi
date: 2006
original_link: https://ieeexplore.ieee.org/document/4106963/
site: ieeeXplore
created_at: 2025-09-11 16:23:03.836799
summary:
  In this effort, we propose a new image fusion technique, utilizing empirical mode decomposition (EMD), for improved face recognition. EMD is a non-parametric data-driven analysis tool that decomposes non-linear non-stationary signals into intrinsic mode functions (IMFs). In this method, we decompose images from different imaging modalities into their IMFs. Fusion is performed at the decomposition level and the fused IMFs are reconstructed to form the fused image. The effect of fusion on face recognition is measured by obtaining the cumulative match characteristics (CMCs) between galleries and probes. Apart from conducting face recognition tests on visible and infrared raw datasets, we use datasets fused by averaging, principal component (PCA) fusion, wavelet based fusion and our method, for comparison. The face recognition rate due to EMD fused images is higher than the face recognition rates due to raw visible, raw infrared and other fused images. Examples of the fused images and illustrative CMC comparison charts are shown.

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title:
  Fusion of Visible and Infrared Images using Empirical Mode Decomposition to Improve Face Recognition


author: J. Park;V. Govindaraju;S.N. Srihari
date: 1999
original_link: https://ieeexplore.ieee.org/document/791860/
site: ieeeXplore
title: Efficient word segmentation driven by unconstrained handwritten phrase recognition
created_at: 2025-09-11 16:23:03.837799
summary:
  An efficient system which finds the best match between an input image and a lexicon is presented. To capture writing style of spacing between words and characters prime stroke analysis based on statistical methods is introduced. A method for estimating bound on number of characters without actual recognition is also presented. For system efficiency, before actual recognition, classified groups of word segments and eligible subset of lexicons are generated as hypotheses. The hypotheses are verified and ordered by a lexicon driven word recognizor. We have tested our approach in the street name recognition/interpretation for US mail stream. Experimental results and encouraging.

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date: 10 September, 2025
original_link: https://arxiv.org/abs/2509.08826
pdf_url: https://arxiv.org/pdf/2509.08826
site: arxiv
title: RewardDance: Reward Scaling in Visual Generation
created_at: 2025-09-11 16:23:03.838799
author:
  Jie Wu;Yu Gao;Zilyu Ye;Ming Li;Liang Li;Hanzhong Guo;Jie Liu;Zeyue Xue;Xiaoxia Hou;Wei Liu;Yan Zeng;Weilin Huang

summary:
  Abstract:Reward Models (RMs) are critical for improving generation models via Reinforcement Learning (RL), yet the RM scaling paradigm in visual generation remains largely unexplored. It primarily due to fundamental limitations in existing approaches: CLIP-based RMs suffer from architectural and input modality constraints, while prevalent Bradley-Terry losses are fundamentally misaligned with the next-token prediction mechanism of Vision-Language Models (VLMs), hindering effective scaling. More critically, the RLHF optimization process is plagued by Reward Hacking issue, where models exploit flaws in the reward signal without improving true quality. To address these challenges, we introduce RewardDance, a scalable reward modeling framework that overcomes these barriers through a novel generative reward paradigm. By reformulating the reward score as the model's probability of predicting a "yes" token, indicating that the generated image outperforms a reference image according to specific criteria, RewardDance intrinsically aligns reward objectives with VLM architectures. This alignment unlocks scaling across two dimensions: (1) Model Scaling: Systematic scaling of RMs up to 26 billion parameters; (2) Context Scaling: Integration of task-specific instructions, reference examples, and chain-of-thought (CoT) reasoning. Extensive experiments demonstrate that RewardDance significantly surpasses state-of-the-art methods in text-to-image, text-to-video, and image-to-video generation. Crucially, we resolve the persistent challenge of "reward hacking": Our large-scale RMs exhibit and maintain high reward variance during RL fine-tuning, proving their resistance to hacking and ability to produce diverse, high-quality outputs. It greatly relieves the mode collapse problem that plagues smaller models.

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author: Jenna Kang;Maria Silva;Patsorn Sangkloy;Kenneth Chen;Niall Williams;Qi Sun
date: 10 September, 2025
original_link: https://arxiv.org/abs/2509.08818
pdf_url: https://arxiv.org/pdf/2509.08818
site: arxiv
title: GeneVA: A Dataset of Human Annotations for Generative Text to Video Artifacts
created_at: 2025-09-11 16:23:03.839802
summary:
  Abstract:Recent advances in probabilistic generative models have extended capabilities from static image synthesis to text-driven video generation. However, the inherent randomness of their generation process can lead to unpredictable artifacts, such as impossible physics and temporal inconsistency. Progress in addressing these challenges requires systematic benchmarks, yet existing datasets primarily focus on generative images due to the unique spatio-temporal complexities of videos. To bridge this gap, we introduce GeneVA, a large-scale artifact dataset with rich human annotations that focuses on spatio-temporal artifacts in videos generated from natural text prompts. We hope GeneVA can enable and assist critical applications, such as benchmarking model performance and improving generative video quality.

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author: Matthieu Vilain;Rémi Giraud;Yannick Berthoumieu;Guillaume Bourmaud
date: 10 September, 2025
original_link: https://arxiv.org/abs/2509.08805
pdf_url: https://arxiv.org/pdf/2509.08805
site: arxiv
title: Handling Multiple Hypotheses in Coarse-to-Fine Dense Image Matching
created_at: 2025-09-11 16:23:03.840808
summary:
  Abstract:Dense image matching aims to find a correspondent for every pixel of a source image in a partially overlapping target image. State-of-the-art methods typically rely on a coarse-to-fine mechanism where a single correspondent hypothesis is produced per source location at each scale. In challenging cases -- such as at depth discontinuities or when the target image is a strong zoom-in of the source image -- the correspondents of neighboring source locations are often widely spread and predicting a single correspondent hypothesis per source location at each scale may lead to erroneous matches. In this paper, we investigate the idea of predicting multiple correspondent hypotheses per source location at each scale instead. We consider a beam search strategy to propagat multiple hypotheses at each scale and propose integrating these multiple hypotheses into cross-attention layers, resulting in a novel dense matching architecture called BEAMER. BEAMER learns to preserve and propagate multiple hypotheses across scales, making it significantly more robust than state-of-the-art methods, especially at depth discontinuities or when the target image is a strong zoom-in of the source image.

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author: Eric Slyman;Mehrab Tanjim;Kushal Kafle;Stefan Lee
date: 10 September, 2025
original_link: https://arxiv.org/abs/2509.08777
pdf_url: https://arxiv.org/pdf/2509.08777
site: arxiv
title: Calibrating MLLM-as-a-judge via Multimodal Bayesian Prompt Ensembles
created_at: 2025-09-11 16:23:03.841806
summary:
  Abstract:Multimodal large language models (MLLMs) are increasingly used to evaluate text-to-image (TTI) generation systems, providing automated judgments based on visual and textual context. However, these "judge" models often suffer from biases, overconfidence, and inconsistent performance across diverse image domains. While prompt ensembling has shown promise for mitigating these issues in unimodal, text-only settings, our experiments reveal that standard ensembling methods fail to generalize effectively for TTI tasks. To address these limitations, we propose a new multimodal-aware method called Multimodal Mixture-of-Bayesian Prompt Ensembles (MMB). Our method uses a Bayesian prompt ensemble approach augmented by image clustering, allowing the judge to dynamically assign prompt weights based on the visual characteristics of each sample. We show that MMB improves accuracy in pairwise preference judgments and greatly enhances calibration, making it easier to gauge the judge's true uncertainty. In evaluations on two TTI benchmarks, HPSv2 and MJBench, MMB outperforms existing baselines in alignment with human annotations and calibration across varied image content. Our findings highlight the importance of multimodal-specific strategies for judge calibration and suggest a promising path forward for reliable large-scale TTI evaluation.

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author: Humera Shaikh;Kaur Jashanpreet
date: 10 September, 2025
original_link: https://arxiv.org/abs/2509.08712
pdf_url: https://arxiv.org/pdf/2509.08712
site: arxiv
title: Computational Imaging for Enhanced Computer Vision
created_at: 2025-09-11 16:23:03.842806
summary:
  Abstract:This paper presents a comprehensive survey of computational imaging (CI) techniques and their transformative impact on computer vision (CV) applications. Conventional imaging methods often fail to deliver high-fidelity visual data in challenging conditions, such as low light, motion blur, or high dynamic range scenes, thereby limiting the performance of state-of-the-art CV systems. Computational imaging techniques, including light field imaging, high dynamic range (HDR) imaging, deblurring, high-speed imaging, and glare mitigation, address these limitations by enhancing image acquisition and reconstruc- tion processes. This survey systematically explores the synergies between CI techniques and core CV tasks, including object detection, depth estimation, optical flow, face recognition, and keypoint detection. By analyzing the relationships between CI methods and their practical contributions to CV applications, this work highlights emerging opportunities, challenges, and future research directions. We emphasize the potential for task-specific, adaptive imaging pipelines that improve robustness, accuracy, and efficiency in real-world scenarios, such as autonomous navigation, surveillance, augmented reality, and robotics.

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date: 10 September, 2025
original_link: https://arxiv.org/abs/2509.08640
pdf_url: https://arxiv.org/pdf/2509.08640
site: arxiv
created_at: 2025-09-11 16:23:03.843806
author:
  Lauren H. Cooke;Matthias Jung;Jan M. Brendel;Nora M. Kerkovits;Borek Foldyna;Michael T. Lu;Vineet K. Raghu

summary:
  Abstract:Chest radiographs (CXRs) are among the most common tests in medicine. Automated image interpretation may reduce radiologists\' workload and expand access to diagnostic expertise. Deep learning multi-task and foundation models have shown strong performance for CXR interpretation but are vulnerable to shortcut learning, where models rely on spurious and off-target correlations rather than clinically relevant features to make decisions. We introduce RoentMod, a counterfactual image editing framework that generates anatomically realistic CXRs with user-specified, synthetic pathology while preserving unrelated anatomical features of the original scan. RoentMod combines an open-source medical image generator (RoentGen) with an image-to-image modification model without requiring retraining. In reader studies with board-certified radiologists and radiology residents, RoentMod-produced images appeared realistic in 93\% of cases, correctly incorporated the specified finding in 89-99\% of cases, and preserved native anatomy comparable to real follow-up CXRs. Using RoentMod, we demonstrate that state-of-the-art multi-task and foundation models frequently exploit off-target pathology as shortcuts, limiting their specificity. Incorporating RoentMod-generated counterfactual images during training mitigated this vulnerability, improving model discrimination across multiple pathologies by 3-19\% AUC in internal validation and by 1-11\% for 5 out of 6 tested pathologies in external testing. These findings establish RoentMod as a broadly applicable tool for probing and correcting shortcut learning in medical AI. By enabling controlled counterfactual interventions, RoentMod enhances the robustness and interpretability of CXR interpretation models and provides a generalizable strategy for improving foundation models in medical imaging.

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title:
  RoentMod: A Synthetic Chest X-Ray Modification Model to Identify and Correct Image Interpretation Model Shortcuts


date: 10 September, 2025
original_link: https://arxiv.org/abs/2509.08624
pdf_url: https://arxiv.org/pdf/2509.08624
site: arxiv
title: UOPSL: Unpaired OCT Predilection Sites Learning for Fundus Image Diagnosis Augmentation
created_at: 2025-09-11 16:23:03.844808
author:
  Zhihao Zhao;Yinzheng Zhao;Junjie Yang;Xiangtong Yao;Quanmin Liang;Daniel Zapp;Kai Huang;Nassir Navab;M. Ali Nasseri

summary:
  Abstract:Significant advancements in AI-driven multimodal medical image diagnosis have led to substantial improvements in ophthalmic disease identification in recent years. However, acquiring paired multimodal ophthalmic images remains prohibitively expensive. While fundus photography is simple and cost-effective, the limited availability of OCT data and inherent modality imbalance hinder further progress. Conventional approaches that rely solely on fundus or textual features often fail to capture fine-grained spatial information, as each imaging modality provides distinct cues about lesion predilection sites. In this study, we propose a novel unpaired multimodal framework \UOPSL that utilizes extensive OCT-derived spatial priors to dynamically identify predilection sites, enhancing fundus image-based disease recognition. Our approach bridges unpaired fundus and OCTs via extended disease text descriptions. Initially, we employ contrastive learning on a large corpus of unpaired OCT and fundus images while simultaneously learning the predilection sites matrix in the OCT latent space. Through extensive optimization, this matrix captures lesion localization patterns within the OCT feature space. During the fine-tuning or inference phase of the downstream classification task based solely on fundus images, where paired OCT data is unavailable, we eliminate OCT input and utilize the predilection sites matrix to assist in fundus image classification learning. Extensive experiments conducted on 9 diverse datasets across 28 critical categories demonstrate that our framework outperforms existing benchmarks.

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date: 10 September, 2025
original_link: https://arxiv.org/abs/2509.08618
pdf_url: https://arxiv.org/pdf/2509.08618
site: arxiv
title: CLAPS: A CLIP-Unified Auto-Prompt Segmentation for Multi-Modal Retinal Imaging
created_at: 2025-09-11 16:23:03.845808
author:
  Zhihao Zhao;Yinzheng Zhao;Junjie Yang;Xiangtong Yao;Quanmin Liang;Shahrooz Faghihroohi;Kai Huang;Nassir Navab;M. Ali Nasseri

summary:
  Abstract:Recent advancements in foundation models, such as the Segment Anything Model (SAM), have significantly impacted medical image segmentation, especially in retinal imaging, where precise segmentation is vital for diagnosis. Despite this progress, current methods face critical challenges: 1) modality ambiguity in textual disease descriptions, 2) a continued reliance on manual prompting for SAM-based workflows, and 3) a lack of a unified framework, with most methods being modality- and task-specific. To overcome these hurdles, we propose CLIP-unified Auto-Prompt Segmentation (\CLAPS), a novel method for unified segmentation across diverse tasks and modalities in retinal imaging. Our approach begins by pre-training a CLIP-based image encoder on a large, multi-modal retinal dataset to handle data scarcity and distribution imbalance. We then leverage GroundingDINO to automatically generate spatial bounding box prompts by detecting local lesions. To unify tasks and resolve ambiguity, we use text prompts enhanced with a unique "modality signature" for each imaging modality. Ultimately, these automated textual and spatial prompts guide SAM to execute precise segmentation, creating a fully automated and unified pipeline. Extensive experiments on 12 diverse datasets across 11 critical segmentation categories show that CLAPS achieves performance on par with specialized expert models while surpassing existing benchmarks across most metrics, demonstrating its broad generalizability as a foundation model.

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author: Prashant Singh Basnet;Roshan Chitrakar
date: 10 September, 2025
original_link: https://arxiv.org/abs/2509.08586
pdf_url: https://arxiv.org/pdf/2509.08586
site: arxiv
title: CNN-ViT Hybrid for Pneumonia Detection: Theory and Empiric on Limited Data without Pretraining
created_at: 2025-09-11 16:23:03.846807
summary:
  Abstract:This research explored the hybridization of CNN and ViT within a training dataset of limited size, and introduced a distinct class imbalance. The training was made from scratch with a mere focus on theoretically and experimentally exploring the architectural strengths of the proposed hybrid model. Experiments were conducted across varied data fractions with balanced and imbalanced training datasets. Comparatively, the hybrid model, complementing the strengths of CNN and ViT, achieved the highest recall of 0.9443 (50% data fraction in balanced) and consistency in F1 score around 0.85, suggesting reliability in diagnosis. Additionally, the model was successful in outperforming CNN and ViT in imbalanced datasets. Despite its complex architecture, it required comparable training time to the transformers in all data fractions.

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author: Jinhan Li;Haoyang He;Lei Xie;Jiangning Zhang
date: 10 September, 2025
original_link: https://arxiv.org/abs/2509.08583
pdf_url: https://arxiv.org/pdf/2509.08583
site: arxiv
title: EfficientIML: Efficient High-Resolution Image Manipulation Localization
created_at: 2025-09-11 16:23:03.847806
summary:
  Abstract:With imaging devices delivering ever-higher resolutions and the emerging diffusion-based forgery methods, current detectors trained only on traditional datasets (with splicing, copy-moving and object removal forgeries) lack exposure to this new manipulation type. To address this, we propose a novel high-resolution SIF dataset of 1200+ diffusion-generated manipulations with semantically extracted masks. However, this also imposes a challenge on existing methods, as they face significant computational resource constraints due to their prohibitive computational complexities. Therefore, we propose a novel EfficientIML model with a lightweight, three-stage EfficientRWKV backbone. EfficientRWKV's hybrid state-space and attention network captures global context and local details in parallel, while a multi-scale supervision strategy enforces consistency across hierarchical predictions. Extensive evaluations on our dataset and standard benchmarks demonstrate that our approach outperforms ViT-based and other SOTA lightweight baselines in localization performance, FLOPs and inference speed, underscoring its suitability for real-time forensic applications.

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author: Chen D.
original_link: https://pubmed.ncbi.nlm.nih.gov/35958758/
site: pubmed
created_at: 2025-09-11 16:23:03.849808
summary:
  Sports athletes are prone to certain injuries during high-intensity exercise training. In the process of treating an injury, images of the injury site need to be collected and identified. However, the traditional recognition method cannot effectively extract the features of the image. At the same time, it ignores the optimization of the damage image recognition results, resulting in low recognition accuracy and poor efficiency. Binocular stereo vision technology can quickly and accurately detect moving objects. Therefore, in order to more accurately identify high-intensity sports injury images, this study takes the high-intensity sports injury images as the basic research object. Several processes of image processing based on binocular stereo vision are analyzed, and the vulnerable parts of the body in high-intensity sports are also studied. Finally, the method in this study is verified. The experimental results show that the method proposed in this study reduces the average error rate by 0.19% compared with the traditional recognition method. It can effectively identify and detect injury images, thereby improving the accuracy and stability of sports injury image identification. The identification time is also shortened accordingly, which has certain practicability and feasibility. In addition, the binocular camera used in this study has high accuracy, and the obtained images of sports injuries are of good quality, which lays a foundation for image detection and recognition.

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title:
  Image Recognition of Sports Athletes' High-Intensity Sports Injuries Based on Binocular Stereo Vision.


author: Andrews TJ, Rogers D, Mileva M, Watson DM, Wang A, Burton AM.
original_link: https://pubmed.ncbi.nlm.nih.gov/37527594/
site: pubmed
title: A narrow band of image dimensions is critical for face recognition.
created_at: 2025-09-11 16:23:03.851806
summary:
  A key challenge in human and computer face recognition is to differentiate information that is diagnostic for identity from other sources of image variation. Here, we used a combined computational and behavioural approach to reveal critical image dimensions for face recognition. Behavioural data were collected using a sorting and matching task with unfamiliar faces and a recognition task with familiar faces. Principal components analysis was used to reveal the dimensions across which the shape and texture of faces in these tasks varied. We then asked which image dimensions were able to predict behavioural performance across these tasks. We found that the ability to predict behavioural responses in the unfamiliar face tasks increased when the early PCA dimensions (i.e. those accounting for most variance) of shape and texture were removed from the analysis. Image similarity also predicted the output of a computer model of face recognition, but again only when the early image dimensions were removed from the analysis. Finally, we found that recognition of familiar faces increased when the early image dimensions were removed, decreased when intermediate dimensions were removed, but then returned to baseline recognition when only later dimensions were removed. Together, these findings suggest that early image dimensions reflect ambient changes, such as changes in viewpoint or lighting, that do not contribute to face recognition. However, there is a narrow band of image dimensions for shape and texture that are critical for the recognition of identity in humans and computer models of face recognition.

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author: Kwak D, Choi J, Lee S.
original_link: https://pubmed.ncbi.nlm.nih.gov/36850906/
pdf_url: https://pmc.ncbi.nlm.nih.gov/articles/PMC9958611/pdf/sensors-23-02307.pdf
site: pubmed
title: Rethinking Breast Cancer Diagnosis through Deep Learning Based Image Recognition.
created_at: 2025-09-11 16:23:03.853806
summary:
  This paper explored techniques for diagnosing breast cancer using deep learning based medical image recognition. X-ray (Mammography) images, ultrasound images, and histopathology images are used to improve the accuracy of the process by diagnosing breast cancer classification and by inferring their affected location. For this goal, the image recognition application strategies for the maximal diagnosis accuracy in each medical image data are investigated in terms of various image classification (VGGNet19, ResNet50, DenseNet121, EfficietNet v2), image segmentation (UNet, ResUNet++, DeepLab v3), and related loss functions (binary cross entropy, dice Loss, Tversky loss), and data augmentation. As a result of evaluations through the presented methods, when using filter-based data augmentation, ResNet50 showed the best performance in image classification, and UNet showed the best performance in both X-ray image and ultrasound image as image segmentation. When applying the proposed image recognition strategies for the maximal diagnosis accuracy in each medical image data, the accuracy can be improved by 33.3% in image segmentation in X-ray images, 29.9% in image segmentation in ultrasound images, and 22.8% in image classification in histopathology images.

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author: Wang S, Wang A, Fu X, Wu K, Lu T.
original_link: https://pubmed.ncbi.nlm.nih.gov/38251798/
site: pubmed
created_at: 2025-09-11 16:23:03.855310
summary:
  In this paper, the directional gradient histogram technology is employed to extract the features of concrete image samples captured under different vibration states. The support vector machine (SVM) is utilized to learn the relationship between image features and vibration state. The machine learning results are subsequently used to assess the feasibility of the concrete vibration state. Simultaneously, the influence mechanism of the calculation parameters of the directional gradient histogram on the recognition accuracy is analyzed. The results demonstrate the feasibility of using the directional gradient histogram-SVM technology to identify the vibration state of concrete. The recognition accuracy initially increases and then decreases as the block size of the directional gradient, or the number of statistical intervals increases. The recognition accuracy also decreases linearly with the increase of the binarization threshold. By using sample images with a resolution of 1024 pixels x 1024 pixels and optimizing the feature extraction parameters, a recognition accuracy of 100% can be attained.

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title:
  Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine.


author: Longmore CA, Santos IM, Silva CF, Hall A, Faloyin D, Little E.
original_link: https://pubmed.ncbi.nlm.nih.gov/27634103/
site: pubmed
title: Image dependency in the recognition of newly learnt faces.
created_at: 2025-09-11 16:23:03.857314
summary:
  Research investigating the effect of lighting and viewpoint changes on unfamiliar and newly learnt faces has revealed that such recognition is highly image dependent and that changes in either of these leads to poor recognition accuracy. Three experiments are reported to extend these findings by examining the effect of apparent age on the recognition of newly learnt faces. Experiment 1 investigated the ability to generalize to novel ages of a face after learning a single image. It was found that recognition was best for the learnt image with performance falling the greater the dissimilarity between the study and test images. Experiments 2 and 3 examined whether learning two images aids subsequent recognition of a novel image. The results indicated that interpolation between two studied images (Experiment 2) provided some additional benefit over learning a single view, but that this did not extend to extrapolation (Experiment 3). The results from all studies suggest that recognition was driven primarily by pictorial codes and that the recognition of faces learnt from a limited number of sources operates on stored images of faces as opposed to more abstract, structural, representations.

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author: Goetschalckx L, Moors J, Wagemans J.
original_link: https://pubmed.ncbi.nlm.nih.gov/31402784/
site: pubmed
title: Incidental image memorability.
created_at: 2025-09-11 16:23:03.859317
summary:
  Recent studies using intentional memory tasks showed that images differ consistently in memorability. Here, we used a surprise recognition memory test. We asked how incidental encoding would affect the consistency and ranking of the memorability scores. If memorability is truly an intrinsic property of the image, one should not expect large differences between incidental and intentional conditions. On the other hand, participants might process images differently when not anticipating a memory test, yielding different results. The study list of our incidental memory task was identical to our previous, intentional study. Participants were to watch the images of this list carefully as they appeared on the screen one by one (free viewing); supposedly for a study about eye movements. Afterwards, a surprise recognition memory test was administered. Despite the free viewing instructions during the study phase, the resulting incidental image memorability scores still showed high levels of consistency across participants. In addition, the overlap between the incidental and intentional memorability ranking was large. These results provide further support for the idea of memorability as an intrinsic image property and add to its ecological validity, as people rarely memorise images intentionally.

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author: Fleming RW.
original_link: https://pubmed.ncbi.nlm.nih.gov/28697677/
site: pubmed
title: Material Perception.
created_at: 2025-09-11 16:23:03.860316
summary:
  Under typical viewing conditions, human observers effortlessly recognize materials and infer their physical, functional, and multisensory properties at a glance. Without touching materials, we can usually tell whether they would feel hard or soft, rough or smooth, wet or dry. We have vivid visual intuitions about how deformable materials like liquids or textiles respond to external forces and how surfaces like chrome, wax, or leather change appearance when formed into different shapes or viewed under different lighting. These achievements are impressive because the retinal image results from complex optical interactions between lighting, shape, and material, which cannot easily be disentangled. Here I argue that because of the diversity, mutability, and complexity of materials, they pose enormous challenges to vision science: What is material appearance, and how do we measure it? How are material properties estimated and represented? Resolving these questions causes us to scrutinize the basic assumptions of mid-level vision.

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original_link: https://pubmed.ncbi.nlm.nih.gov/39357746/
site: pubmed
created_at: 2025-09-11 16:23:03.862316
author:
  Kishi T, Kobayashi K, Sasagawa K, Sakimura K, Minato T, Kida M, Hata T, Kitagawa Y, Okuma C, Murata T.

summary:
  The novel object recognition test (NORT) is one of the most commonly employed behavioral tests in experimental animals designed to evaluate an animal's interest in and recognition of novelty. However, manual procedures, which rely on researchers' observations, prevent high throughput analysis. In this study, we developed an automated analysis method for NORT utilizing machine learning-assisted exploratory behavior detection. We recorded the exploratory behavior of the mice using a video camera. The coordinates of the mouse nose and tail base in recorded video files were detected using a pre-trained machine learning model, DeepLabCut. Each video was then segmented into frame images, which were categorized into "exploratory," or "non-exploratory" frames based on manual observation. Mouse feature vectors were calculated as vectors from the nose to the vertices of the object and were utilized for SVM training. The trained SVM effectively detected exploratory behaviors, showing a strong correlation with human observer assessments. Upon application to NORT, the duration of mouse exploratory behavior towards objects predicted by the SVM exhibited a significant correlation with the assessments made by human observers. The novelty discrimination index derived from the SVM predictions also aligned well with that from human observations.

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title:
  Automated analysis of a novel object recognition test in mice using image processing and machine learning.


author: Wang W, Zhang C, Tian J, Ou J, Li J.
original_link: https://pubmed.ncbi.nlm.nih.gov/32695155/
pdf_url: https://pmc.ncbi.nlm.nih.gov/articles/PMC7368189/pdf/CIN2020-8859172.pdf
site: pubmed
title: A SAR Image Target Recognition Approach via Novel SSF-Net Models.
created_at: 2025-09-11 16:23:03.863316
summary:
  With the wide application of high-resolution radar, the application of Radar Automatic Target Recognition (RATR) is increasingly focused on how to quickly and accurately distinguish high-resolution radar targets. Therefore, Synthetic Aperture Radar (SAR) image recognition technology has become one of the research hotspots in this field. Based on the characteristics of SAR images, a Sparse Data Feature Extraction module (SDFE) has been designed, and a new convolutional neural network SSF-Net has been further proposed based on the SDFE module. Meanwhile, in order to improve processing efficiency, the network adopts three methods to classify targets: three Fully Connected (FC) layers, one Fully Connected (FC) layer, and Global Average Pooling (GAP). Among them, the latter two methods have less parameters and computational cost, and they have better real-time performance. The methods were tested on public datasets SAR-SOC and SAR-EOC-1. The experimental results show that the SSF-Net has relatively better robustness and achieves the highest recognition accuracy of 99.55% and 99.50% on SAR-SOC and SAR-EOC-1, respectively, which is 1% higher than the comparison methods on SAR-EOC-1.

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author: Han S, Shi Z, Shi Y.
original_link: https://pubmed.ncbi.nlm.nih.gov/35909856/
pdf_url: https://pmc.ncbi.nlm.nih.gov/articles/PMC9328983/pdf/CIN2022-2586042.pdf
site: pubmed
created_at: 2025-09-11 16:23:03.864316
summary:
  The development in technology has resulted in the utilization of artificial intelligence systems in various fields. In this research, we are going to study cultural and creative product design and image recognition based on a convolutional neural network (CNN) model. A convolutional neural network is referred to as a type of artificial neural network (ANN) that is used to analyze visual images. Our proposed system deploys a convolutional neural network model for image recognition in the field of cultural and creative product design. Cultural and creative products are becoming more popular these days. The cultural and creative products are referred to as innovative products or innovative new product design which makes use of the cultural symbols and other cultural factors in their design. In simple words, it is the integration of culture and creativity in a new product design. The main aspect of cultural creative products is the incorporation of cultural features into a new product, thus obtaining a creative- and culture-based product. The study results have proved that CNN has provided an accuracy of 87%.

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title:
  Cultural and Creative Product Design and Image Recognition Based on the Convolutional Neural Network Model.


author: 骆肇阳;董琪;杨阳;刘莹;齐轩宁
date: 2025-08-15
keywords: 智能遮阳;;强化学习;;人工智能;;光环境舒适;
source: 照明工程学报
site: 知网
title: 基于动态规划算法的智能遮阳百叶视觉舒适性能调控研究
created_at: 2025-09-12 17:19:50.876187
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kfvmnz2JoF5efj7XwJXOcn1R4wkLGJzk0UAAiu9ZCrYdW4v0iR6ocstCuuOxvCKUF2Jgg-wVtKua7MpLgMvZ7ClbO_KilehsF77ubAMduf1tZOxlQVrke60Tz256jPLR_TFF9kHDCqOrBKRbgmossC1Fda-tjuXlHWanMVjw5tcYg==&uniplatform=NZKPT&language=CHS

summary:
  智能有效的遮阳百叶调控能够应对动态光环境变化、持续营造视觉舒适的视觉光环境。既有调控系统因室内光环境视觉舒适指标影响机理不清晰，对于室内光环境动态预测能力和智能决策能力不足。本研究结合机器学习技术和强化学习中的动态规划算法，构建室内光环境动态预测模型和智能体，解决室内光环境动态预测非线性拟合不足和调控精度不足的瓶颈。实现智能遮阳百叶在舒适性能上有效调控。

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author: 曹锋;辛莅祚;朱梦瑶
date: 2025-08-08 10:02
keywords: 地铁车站;;人流密度;;通道拥挤度;;通道可用性;;疏散路径网络;;疏散路径动态规划;
source: 现代城市轨道交通
site: 知网
title: 火灾场景下地铁车站人员安全疏散路径动态规划方法
created_at: 2025-09-12 17:19:50.879043
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kfDHCced4Y4pKBvglN_F1uB7SRTdIwzS5dVpuMDkoPju2HG5Q7hYa5DvB64_RUb09esz_loerrunNapjLHoi8w6t1ogSXHvEEqCsvkaFVtsAWDn3GhGc5_1imEgM0WLi33XiOHQfR1X24fWNldNfuSXUKa6mIYZN03DhnEWaRNbwA==&uniplatform=NZKPT&language=CHS

summary:
  针对地铁车站火灾场景下人员疏散需求，文章提出一种基于多源动态数据的智能疏散决策方法。该方法综合考虑地铁车站建筑结构和视频监控设备部署位置，构建车站人员疏散路径网络模型。结合火灾发生位置信息以及火灾烟气蔓延的影响，制定安全疏散路径规划策略，并基于实时人流密度、疏散通道拥挤度和通道可用性等关键指标，提出动态规划方法。以温州地铁S1线某车站为例，设置2种火灾发生场景，将火源点位置和监控视频统计的人流数据作为输入。在路径拥挤度和烟气蔓延影响通道可用性的约束下，利用改进型Dijkstra算法动态产生车站人员安全疏散路径。通过对车站关键位置人流密度和烟气蔓延影响路径安全的实时监测，以及安全疏散路径拥挤度的动态计算，有效解决火灾时因人员恐慌导致的局部严重拥堵问题，提高人员安全疏散效率。该方法可为地铁车站智慧安全疏散管理提供指导性措施和建议。

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author: 周慧灵
date: 2025-08-01
source: 中国储运
site: 知网
title: 基于动态规划的中国生鲜蔬菜物流成本运输最优化方案
created_at: 2025-09-12 17:19:50.880991
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kd5qNvDr6_A1juXN-EhfED0Ocod3EJHcoS7UI04P73g8uKK3u4RNj8i4EMfvh09Kw1U5bwzx9WxWUBtrujXs09lNv3y8xxxXhDPMymonIAXCzmBrdXwJJ1_V7psS2NvKRnLhwdHK6a9iyrVwBR8vznLP1ro9tVC-8nH6v_VGsRNEQ==&uniplatform=NZKPT&language=CHS

summary:
  <正>本研究以商超蔬菜经销为背景，结合动态规划等方法，构建了蔬菜商品最优定价与补货量的收益最大化模型。首先，运用线性回归方法预测了未来蔬菜销售量，并建立了最大收益非线性规划模型，以确定最佳补货量和定价策略。进一步，统计分析了可售品种的利润，并运用背包问题思想建立了动态规划模型，得出了单品补货量和定价策略。最后，综合考虑了市场需求波动、季节性更替、消费者需求和商超竞争关系等因素对补货量和定价策略的影响。该研究为商超蔬菜经销提供了优化决策参考，有助于提高经济效益和市场竞争力。

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author: 于希涛
date: 2025-07-14
keywords: 数据可视化;;动态规划;;航空货运;;航线路径设计;
source: 中国航务周刊
site: 知网
summary: 针对航空货运中转频次高、航班波动大、夜间利用率低及清关效率不足等问题，本文对采用动态规划方法构建多阶段航线优化模型进行探讨，以期为跨境电商航空货运提供兼顾时效性与经济性的航线规划方法。
title: 融合数据可视化与动态规划的航空货运航线路径设计
created_at: 2025-09-12 17:19:50.882565
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kdyMYymMGwq1s-XSu8RlUH8FB3A9su7DV6mFuuCKOuskYuWwCE3BRhsWoL2ZGnv9435YwVS7KrbFUcEYs-g8FqBwWpyspOp6kjdkaP-OyP7CFoh5dHRFtsNm11C9kuc1LZjagH6j08LCFjMGGcgN1MEy8hnGJvbHXl2XpIiOGyNYw==&uniplatform=NZKPT&language=CHS

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author: 李钰瑾;杜玫;李昊天;胡鑫
date: 2025-07-11
keywords: 动态规划;;作物种植优化;;模拟退火算法;;马尔可夫决策模型;
source: 农村实用技术
site: 知网
title: 基于动态规划的作物种植优化决策模型
created_at: 2025-09-12 17:19:50.883902
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kdBcYmkTozdQG1JsTFvEoXM1ip5pH_BoFM5iCcwCXYE-zF2ck3P9xW8sPOKDmAUz9N_QaTF0qt2tMS8IA7zaIrKWAax_SMkrmWmGnwK9q3r0tOy_uL17oPum47FZQgEk2MoqEjsk3D6ABnxnxSr6kJk8PIIo29nMvOwUGsn9sJOaw==&uniplatform=NZKPT&language=CHS

summary:
  基于市场需求，充分利用有限的耕地资源实现作物利润最大的作物种植决策尤为重要。本文针对作物的习性和生长规律，开展了作物种植优化研究。首先以最大收益作为目标，建立单目标规划决策模型；在此基础上，基于动态规划建立马尔可夫决策模型，选用最大化价值函数开展优化策略的迭代计算；这为提高作物的生产效益提供了有效手段，对于促进乡村经济的长期健康发展具有重要的现实意义。

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author: 陈登峰;罗开平;孙剑飞
date: 2025-07-04 09:06
keywords: 柔性工艺流程优化;;离散差分进化算法;;动态规划;;局部搜索策略;
source: 计算机集成制造系统
site: 知网
title: 基于离散差分进化与动态规划的柔性工艺流程双层优化框架
created_at: 2025-09-12 17:19:50.884987
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kdBcYmkTozdQG1JsTFvEoXMZ0G50eMzhy7CfIzQhSDloU1D3qLHvQMJ5PtAOUzXeoZHPwiQfT5aVaK89HJhueZXkc3kcupRdB1_HyQ0uHG49sD2IzGqopluAkKDX-WNJ3t9QqeGJ9dot8_TYNB97mtaZjQeuo_3Ruhl3vgiNa2Ejg==&uniplatform=NZKPT&language=CHS

summary:
  针对柔性工艺流程优化问题（FPP）的可分阶段决策性和多决策要素耦合性，提出一种新的双层优化求解框架。在这种新的框架下，外层采用离散差分进化求解具有NP-hard特性的工序排序子问题；内层采用动态规划求解无后效性的加工资源分配子问题。基于这种双层优化框架，进一步从理论上给出了工艺路线的局部最优性条件，为算法局部搜索提供了精确指导。这种融合随机搜索与精确迭代的双层架构将FPP问题的组合解空间有效地分离成了两个子空间。通过解的合成与评价反馈进行交互，显著降低了求解大规模问题的难度。实验结果表明，提出的算法在解的质量和收敛速度方面均显著优于现有其他算法，尤其在求解大规模问题时优势更加明显。

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author: 曾楚健
date: 2025-06-30
source: 广东工业大学
site: 知网
title: 基于自适应动态规划的非线性系统容错控制方法研究
created_at: 2025-09-12 17:19:50.886011
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kfigSAR7M4yE6jLu4Kt8mv0sUA2f7EJehi9XRmEmN1UTCcy5dr7nJdaO8cKt6pW5tugTq75sHZ4g7GKOZmSVB6PbAHkN6Dv6taS7JjEBsvDztGhhDYAxQQoM11HQi-1LPvMDf0-PSjnEF5PMRbd3VJBgurbtzWqNfA-aSOKuPrApw==&uniplatform=NZKPT&language=CHS

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author: 刘斌;史春生
date: 2025-06-25
keywords: 二氧化碳;;地质封存;;动态规划;;最佳注入井位置;;封存量;
source: 工程科学学报
site: 知网
title: 基于动态规划的碳封存注入井位置优化
created_at: 2025-09-12 17:19:50.886869
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kfigSAR7M4yE6jLu4Kt8mv0cYiX_3ZzS2frWU9RMBpbPh_iJ15HdRmO1-m-cCvX3lcCjbyKVIRg4O_qmgWRkQnM7oxRTrRolDdcZtYl1yzlG790KCvFWKs9uTTEIEdt90tEINUitQ6g1e5LP-NQ7030IbmtDqn7eAtX2S_oW9uEgg==&uniplatform=NZKPT&language=CHS

summary:
  二氧化碳地质封存是降低碳排放、减小温室效应的重要手段之一，是地球科学研究的新兴领域.注入井位置的选择对CO2封存量有重要影响，且受地质条件复杂性和施工条件限制，因而注入井位置的选取是一个复杂的优化问题.本文基于几何方法和渗流理论构建了CO2地质封存模型，结合地层圈闭、溢出路径及溢出点等条件估计地层的封存能力.在此基础上，将CO2地质封存注入井位置优化问题转化为动态规划问题，通过计算最优子结构和状态转移方程，从而确定最佳注入井位置.利用动态规划法优化注入井位置，实现碳封存量最大化，将其用于挪威Utsira储层封存量估计和注入井位置优化，从而为CO2地质封存注入井位置的选择提供理论指导.

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author: 赫强
date: 2025-06-25
source: 汽车画刊
site: 知网
title: 基于动态规划的燃料电池车能量管理策略
created_at: 2025-09-12 17:19:50.887639
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4keqr0dlEI2qGayuGjGi4keHcHt84Skb9bHtNladiMGhLzR9G67rSRFn2Ezcur_BvF2c7MgInDBwX8nbNQiJEM_UPVaya1KsmrOv-dBb5gj3d4rpxBBz3h6yS0qovOz-mAm6Ie20OTcOooAdXTgtzcyj8ZZaptIDhdYhdNjPI7szgw==&uniplatform=NZKPT&language=CHS

summary:
  <正>随着能源短缺与环境污染问题加剧，燃料电池车因其零排放（仅排放水）和高效能特性成为新能源汽车发展的重要方向。能量管理策略作为燃料电池车的核心技术，直接影响能源效率、续航里程及系统寿命。其核心目标是通过优化燃料电池与蓄电池的功率分配，使燃料电池工作在高效区间，同时利用蓄电池快速响应特性，降低氢耗并延长部件寿命。动态规划算法通过多阶段决策的全局优化能力，可精确求解功率分配问题。文章深入研究动态规划的燃料电池车能量管理策略，对推动新能源汽车技术发展、促进能源结构转型具有重要意义。

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author: 王朝晖;邓洋
date: 2025-06-25
keywords: 流水施工;;动态规划;;最短路线;;表达方式;;计算方法;
source: 四川建筑科学研究
site: 知网
title: 无节奏流水施工动态规划组织方法
created_at: 2025-09-12 17:19:50.888332
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kcj0OCaq6B_QchycbghEf5mWxi5uXyjnFk8HABGxmProOwFmutVYxONzraYSwGC-E0LXXsLKgNA-ZlfbgtBvTBg-eo7IWS32JNcw_s7GZFXpA0WK7lp9W1S7bDlMn2u6ek2P0a1Libx-lSZKl0iNea0F5oq1CGdqLqwf_aY59C2kg==&uniplatform=NZKPT&language=CHS

summary:
  无节奏流水施工是广泛应用的施工组织模式，最短路线模型是采用动态规划方法组织流水施工的一种有效工具。介绍了流水施工最短路线模型的建立方法，提出了模型参数的数组表达方法，定义了一种矩阵加列向量的计算规则，从而使最短路线模型计算过程简单明晰；提出了通路法确定最短路线，可以方便地搜索到全部最短路线。算例表明，无节奏流水施工有多种组织方式，不同组织方式下，施工总工期、流水步距都是相同的。

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author: 李端;钱富才;李力
date: 2007年8期
keywords: 动态规划;多目标优化;不可分优化问题;多阶段均值-方差组合投资
quote: 82
source: 《系统工程理论与实践》
site: 万方
title: 动态规划问题研究
created_at: 2025-09-12 17:19:50.888970
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISEnh0Z2NsbHlzajIwMDcwODAwOBoIcHVtbzZpOWk%3D

summary:
  回顾动态规划在过去一些年的发展,特别是它在多目标优化与不可分优化问题中的可喜进展.介绍了动态规划在解决多阶段均值-方差组合投资问题中的创造性应用.旨在进一步推动动态规划的理论研究,拓广它在各行各业中的应用.

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author: 罗党;刘思峰
date: 2004年4期
keywords: 区间灰数;可能度;动态规划;最优解
quote: 34
source: 《系统工程理论与实践》
site: 万方
title: 灰色动态规划研究
created_at: 2025-09-12 17:19:50.889527
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISEnh0Z2NsbHlzajIwMDQwNDAwOBoIcHVtbzZpOWk%3D

summary:
  在普通动态规划的基础上融合灰色系统的思想和方法,运用分析技巧,提出了灰色动态规划、θ动态定位规划及其最优解的概念,构建了灰色动态规划及θ动态定位规划最优解的算法,为动态规划的应用研究提供了新的思路.通过算例说明了算法的合理性与可行性.

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author: 师明;高宇辉;张弓
date: 2024年2期
keywords: 分层任务网络;动态规划;虚拟指令;遥操作
quote: 0
source: 《系统工程与电子技术》
site: 万方
title: 基于HTN的巡视器动态规划方法
created_at: 2025-09-12 17:19:50.890029
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISEnh0Z2N5ZHpqczIwMjQwMjAyNhoIcHVtbzZpOWk%3D

summary:
  为提升深空探测任务中巡视器动态规划处理效率,从航天工程实践经验出发,结合分层任务网络(hierarchical task network,HTN)理论研究成果,提出巡视器领域知识建模方法以及动态规划流程.针对经典动作规划系统不能处理时态约束关系的问题,在建模中引入受限状态事件的表示方法.针对动态规划中的时态约束关系,拓展Allen区间代数的定义,提出事件、全局时间点和虚拟事件的时序逻辑判断方法.针对动态规划中存在的状态空间一致性问题,提出虚拟指令继承原有状态空间的方法.研究结果完善了 HTN在航天领域的知识建模方法,解决了经典动作规划缺少时间信息约束的缺陷.所提出的虚拟事件、虚拟指令解决动态规划状态判定方法,可有效提高深空探测任务中巡视器遥操作的工作效能和地面中心进行事件处理的灵活性.

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author: 刘斌;史春生
date: 2025年6期
keywords: 二氧化碳;地质封存;动态规划;最佳注入井位置;封存量
quote: 0
source: 《工程科学学报》
site: 万方
title: 基于动态规划的碳封存注入井位置优化
created_at: 2025-09-12 17:19:50.890614
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISEWJqa2pkeHhiMjAyNTA2MDE4GghwdW1vNmk5aQ%3D%3D

summary:
  二氧化碳地质封存是降低碳排放、减小温室效应的重要手段之一,是地球科学研究的新兴领域.注入井位置的选择对CO2封存量有重要影响,且受地质条件复杂性和施工条件限制,因而注入井位置的选取是一个复杂的优化问题.本文基于几何方法和渗流理论构建了CO2地质封存模型,结合地层圈闭、溢出路径及溢出点等条件估计地层的封存能力.在此基础上,将CO2地质封存注入井位置优化问题转化为动态规划问题,通过计算最优子结构和状态转移方程,从而确定最佳注入井位置.利用动态规划法优化注入井位置,实现碳封存量最大化,将其用于挪威Utsira储层封存量估计和注入井位置优化,从而为CO2地质封存注入井位置的选择提供理论指导.

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author: 毕龙阁
date: 2018年17期
keywords: 动态规划;最优解
quote: 0
source: 《数字化用户》
site: 万方
title: 浅谈动态规划
created_at: 2025-09-12 17:19:50.891076
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDnN6aHloMjAxODE3MjAyGghwdW1vNmk5aQ%3D%3D

summary:
  对于一些寻找最优解的问题,我们常常使用贪心算法,因为这个算法比较符合人们的日常思维,总是按照当前最优的情况去选择.但是对于一些比较难解的问题我们用贪心的算法通常是没有办法的到最优解的.这时候我们就需要考虑使用别的策略了.动态规划是求解一类问题的策略,本文通过一个例子来分析一下最优问题是怎么用动态规划解决的.

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author: 许扬灵
date: 2001年4期
keywords: 有向图;动态规划;目标函数;递归函数
quote: 0
source: 《南京师大学报（自然科学版）》
site: 万方
summary: 在集合论的基础上将离散的动态规划形式化,用递归函数刻划了动态规划的目标函数,并在有向图上建立了动态规划.推广了动态规划方法的应用范围.
title: 有向图上的动态规划
created_at: 2025-09-12 17:19:50.891513
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISEG5qc2R4YnoyMDAxMDQwMDUaCHB1bW82aTlp

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author: 王硕;吴维敏;张涛
date: 2025年1期
keywords: 网联车;车辆调度;背压算法;车辆路线动态规划;交通拥堵
quote: 0
source: 《东北大学学报（自然科学版）》
site: 万方
title: 基于改进背压算法的车辆路线动态规划方法
created_at: 2025-09-12 17:19:50.891928
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISD2RiZHh4YjIwMjUwMTAwMxoIcHVtbzZpOWk%3D

summary:
  为了缓解交通网络中的拥堵,提出了一种基于网联车密度和速度背压的车辆调度方法.考虑道路上车辆的复杂性和异质性,通过计算上、下游道路的车辆密度来确定背压值,并使用道路的最大通行速度作为权重.根据背压的比率调整上游车队分配至下游道路的车辆数量,从而实现车流的均衡分布.此外,以最小化车队行驶距离为优化目标确定单个车辆路线计划,以减少车辆的平均行驶距离.仿真结果表明,该方法比其他基于背压算法的路线动态规划方法,能有效减少交通网络中排队车辆的数量,从而降低交通拥堵,同时也缩短了车辆的平均行驶距离和时间.

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author: 康子旭;周栋;李会欣
date: 2024年1期
keywords: 备件;飞机状态;马尔可夫生灭过程;经济性;动态规划
quote: 4
source: 《北京航空航天大学学报》
site: 万方
title: 基于飞机状态的备件动态规划技术
created_at: 2025-09-12 17:19:50.892334
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISE2JqaGtodGR4eGIyMDI0MDEwMjgaCHB1bW82aTlp

summary:
  伴随民航业的竞争日趋激烈,航空公司迫切需要控制成本以提升效益.民机备件既是直接影响飞行安全的关键因素,备件成本又在航空公司可控成本中占比最高.因此,在保证飞行安全的前提下做好备件规划,对航空公司有至关重要的意义.根据民机备件的安全级别、故障修复时限等对备件分级设置保障率水平,采用符合备件故障特性的马尔可夫生灭过程,建立满足给定保障率水平的备件量计算模型,并在此基础上建立以保障成本最低为目标函数,满足保障率水平为约束函数的备件量动态规划模型.基于飞机状态分析历史故障数据、季节性、日利用率、机队规模对备件保障的影响,在所建模型中将故障率季节性差异、日利用率和飞机停场损失淡旺季差异进行评估以减小计算结果与实际需求的偏差.以H航空公司ERJ-190机型显示组件为例,对所建模型进行应用验证,计算结果与H航空公司运营实际相吻合,证明所建模型可为航空公司备件规划提供技术方法支持.

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author: 祁文青
date: 2002年4期
keywords: 阶段;状态;决策
quote: 10
source: 《黄石高等专科学校学报》
site: 万方
title: 动态规划
created_at: 2025-09-12 17:19:50.892741
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISE2hzZ2R6a3h4eGIyMDAyMDQwMDgaCHB1bW82aTlp

summary:
  动态规划是解决多阶段决策最优化问题的一种思想方法.所谓"动态",指的是在问题的多阶段决策中,按某一顺序,根据每一步所选决策的不同,将随即引起状态的转移,最终在变化的状态中产生一个决策序列.动态规划就是为了使产生的决策序列在符合某种条件下达到最优.

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author: 何雯晴;唐亮
date: 2025年6期
keywords: 共享制造;动态定价;近似动态规划
quote: 0
source: 《计算机集成制造系统》
site: 万方
title: 基于近似动态规划的共享制造平台订单动态定价优化
created_at: 2025-09-12 17:19:50.893164
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISEmpzampjenp4dDIwMjUwNjAyNRoIcHVtbzZpOWk%3D

summary:
  针对平台下的运营管理问题,结合共享制造环境下客户需求的动态性和随机性特征,研究有限期内共享制造平台生产订单的动态定价优化问题.基于有限的制造设备产能资源,以共享制造平台利润最大化为目标,建立随机动态规划模型.采用近似动态规划方法将原始动态规划问题转换为等价的线性规划,针对线性规划中状态和决策维数过高的问题,以制造设备可用时间点为基函数,构建仿射近似函数近似状态价值,并以贪婪策略作为约束采样方法采样状态和决策集合,有效地减少了约束数量,得到了订单动态定价策略.通过不同参数设置下的仿真实验,验证了订单动态定价策略的稳定性和有效性.

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author: Xiaofeng Lin;Nuyun Cao;Yuzhang Lin
date: 2013
original_link: https://ieeexplore.ieee.org/document/6615005/
site: ieeeXplore
created_at: 2025-09-12 17:19:50.893573
summary:
  In this paper, a finite-horizon ε-optimal control for a class of nonlinear systems with state delay is proposed by Adaptive Dynamic Programming (ADP) algorithm. First of all, the performance index function is defined and the Hamilton-Jacobi-Bellman (HJB) equation is obtained for the problem, the convergence of the iterative algorithm is also presented. Then, ADP algorithm for finite-horizon optimal control is introduced with an ε-error bound so as to get the ε-optimal control, and BP neural network is used to implement ADP algorithm. At last, an example is given to demonstrate the effectiveness of the proposed algorithm.

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title:
  Optimal control for a class of nonlinear systems with state delay based on Adaptive Dynamic Programming with ε-error bound


author: Asma Al-Tamimi;Frank Lewis
date: 2007
original_link: https://ieeexplore.ieee.org/document/4220812/
site: ieeeXplore
title: Discrete-time nonlinear HJB solution using Approximate dynamic programming: Convergence Proof
created_at: 2025-09-12 17:19:50.893981
summary:
  In this paper, a greedy iteration scheme based on approximate dynamic programming (ADP), namely heuristic dynamic programming (HDP), is used to solve for the value function of the Hamilton Jacobi Bellman equation (HJB) that appears in discrete-time (DT) nonlinear optimal control. Two neural networks are used - one to approximate the value function and one to approximate the optimal control action. The importance of ADP is that it allows one to solve the HJB equation for general nonlinear discrete-time systems by using a neural network to approximate the value function. The importance of this paper is that the proof of convergence of the HDP iteration scheme is provided using rigorous methods for general discrete-time nonlinear systems with continuous state and action spaces. Two examples are provided in this paper. The first example is a linear system, where ADP is found to converge to the correct solution of the algebraic Riccati equation (ARE). The second example considers a nonlinear control system.

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author: Song Shao-jian;Li Xiao-qiang;Lin Xiao-feng;Liao Bi-lin
date: 2009
original_link: https://ieeexplore.ieee.org/document/5191555/
site: ieeeXplore
title: Adaptive neural controller design for synchronous generator based on Heuristic Dynamic Programming
created_at: 2025-09-12 17:19:50.894400
summary:
  Synchronous generator is a system which has a series of dynamic characteristics as non-linear, fast response and so on. It ensures the stability and security of the power grid and plays an important role. As a result, the effective control of the synchronous generator, it is particularly important. This paper provides a new type of adaptive neural controller, which is based on heuristic dynamic programming (HDP) method. It can be updated on-line, and constantly optimize the controller. Illustrated by the case of the single machine infinite bus system, the simulation of neural controller and the traditional automatic voltage regulator about phase short-circuit is carried out using Matlab/Simulink. The result shows that the new type of controller is more effective.

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author: Tai-Gui Qin;Wei Huang;Gao-Xia Wang
date: 2010
original_link: https://ieeexplore.ieee.org/document/5571362/
site: ieeeXplore
title: The Application of Dynamic Programming in the Nonlinear Programming Problems
created_at: 2025-09-12 17:19:50.894801
summary:
  In this paper, the authors introduced the optimally principle of the dynamic programming and discussed the problem-solving steps. Using the MATLAB programming, solved two constrained nonlinear programming problem and obtained the preferred plans.

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author: Xiaofeng Lin;Zhigang Zhang;Derong Liu
date: 2007
original_link: https://ieeexplore.ieee.org/document/4370980/
site: ieeeXplore
title: Temperature Control in Precalcinator with Dual Heuristic Dynamic Programming
created_at: 2025-09-12 17:19:50.895209
summary:
  In cement manufacturing, pre-calcining process (PCP) contains an added precalcinator between the preheater and the kiln. Since raw meal decomposition rate in the kiln is over 90%, optimal control is necessary for keeping the temperature stable to ensure normal decomposition. Due to the diversity of raw meal composition and the consistent thermal transformation, temperature control in the precalcinator is a complex nonlinear control problem. Many factors may influence it, and there are couplings between various factors and uncertainties. It is difficult to solve the dynamic stability control problem for the temperature in precalcinator. This paper addresses temperature control in the precalcinator using dual heuristic dynamic programming (DHP). The approach is mainly composed of three parts: model network, action network and critic network. All three parts use neural networks (NN) to simulate the temperature trend. The self-learning and adaptive abilities were analyzed in the MATLAB environment and simulation results demonstrate the advantage of adaptation and optimization solutions compared to conventional control.

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date: 1996
original_link: https://ieeexplore.ieee.org/document/6078135/
site: ieeeXplore
title: Dynamic programming method to optimize control rod positions in NHR-200
created_at: 2025-09-12 17:19:50.895638
summary:
  A code. OPTROD. based on dynamic programming method is developed and utilized to optimize control rod positions throughout the fuel cycle of the 200 MW nuclear heating reactor (NHR-200). A fuel cycle is divided into many steps or stages. Optimization of the multistage process is solved iteratively in the forward direction throughout a fuel cycle. The dynamic programming method is much more efficient than the normal nonlinear programming method. Convergence is obtained even if poor initial control rod positions are given.

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author: Xiaofeng Lin;Qiang Ding;Weikai Kong;Chunning Song;Qingbao Huang
date: 2014
original_link: https://ieeexplore.ieee.org/document/7010638/
site: ieeeXplore
created_at: 2025-09-12 17:19:50.896049
summary:
  For the optimal tracking control problem of affine nonlinear systems, a general value iteration algorithm based on adaptive dynamic programming is proposed in this paper. By system transformation, the optimal tracking problem is converted into the optimal regulating problem for the tracking error dynamics. Then, general value iteration algorithm is developed to obtain the optimal control with convergence analysis. Considering the advantages of echo state network, we use three echo state networks with levenberg-Marquardt (LM) adjusting algorithm to approximate the system, the cost function and the control law. A simulation example is given to demonstrate the effectiveness of the presented scheme.

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title:
  Adaptive dynamic programming-based optimal tracking control for nonlinear systems using general value iteration


author: Yuan-bin Yu;Qing-nian Wang;Yong-jiu Chen;Chang-jian Hu;Bo-shi Wang
date: 2009
original_link: https://ieeexplore.ieee.org/document/5164375/
site: ieeeXplore
created_at: 2025-09-12 17:19:50.896452
summary:
  Dynamic Programming (DP) algorithm is used to find the optimal trajectories under Beijing cycle for the power management of synergic electric system which composed of batteries and super capacitors. Feasible rules are derived from analyzing the optimal trajectories, and it is shown that the highest contribution of Synergic Electric System (SES) to the HEV and the methods of how to get the best performance of it. Using the new Rule-based power management strategy adopted from the optimal results, it is easy to demonstrate the effectiveness of new strategies in further improving the fuel economy of the synergic hybrid system.

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title:
  Control strategy optimization research using Dynamic Programming method for Synergic Electric System on HEV


author: Zhen Lei;Yan Sun;Yun-han Song;Dong Li
date: 2015
original_link: https://ieeexplore.ieee.org/document/7373799/
site: ieeeXplore
created_at: 2025-09-12 17:19:50.896875
summary:
  This paper takes the operational test credibility as the analysis object, designs multi-stage test patterns through quantitative decision analysis, thus maximizes the system test credibility. A dynamic programming based model for the credibility of equipment operational test is established. In addition, a method based on the 0-1 integer linear programming is also used and transformed to fit for the minimum path problem. The experimental results indicate that the methods proposed by this paper are effective and advanced.

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title:
  The Quantitative Analysis of Equipment Operational Test Credibility Based on Dynamic Programming and 0-1 Integer Linear Programming


author: Yi-Min Wang;Tao Sun;Song Ma;Lei-Ming He
date: 2023
original_link: https://ieeexplore.ieee.org/document/10240369/
site: ieeeXplore
title: An Improved Data-Driven Adaptive Dynamic Programming Approach for Cooperative Games
created_at: 2025-09-12 17:19:50.897282
summary:
  In this paper, we consider a continuous system cooperative dynamic game problem with two players. Through the introduction of dynamic programming concept, a Hamilton-jacobi-Belman equation for two players is designed. By introducing detection noises and using the basis function approximation method, a data-driven adaptive dynamic programming method is proposed and an iterative equation is obtained. Then, by introducing two detection noises and using the basis function approximation method, an iterative equation is obtained. It is note-worthy that we can obtain the Nash equilibrium solution of the cooperative game. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed adaptive dynamic programming approach.

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author: Sophie Crisp;R. Joel England;Alexander Ody;Pietro Musumeci
date: 9 September, 2025
original_link: https://arxiv.org/abs/2509.08170
pdf_url: https://arxiv.org/pdf/2509.08170
site: arxiv
created_at: 2025-09-12 17:19:50.897683
summary:
  Abstract:Progress in optical techniques has made precision control of the phase profile in optical pulses common and accessible in scientific laboratories. Carefully shaping the field profile of a laser pulse can be used to master the dynamics of electrons traveling in photonic accelerating structures such as the ones obtained by precisely aligning two dielectric gratings. Here we show that by applying a liquid-crystal-mask to program the phase and amplitude of an infrared laser pulse in combination with a pulse front tilt scheme, it is possible to implement dynamic control on a laser accelerator. This results in a nearly limitless live tuning capability of the accelerator beam dynamics, allowing the demonstration software-based correction of structure and optical front imperfections, implementation of transverse focusing schemes, control of the energy and charge of the output beam, and ultimately optimization of the interaction length, leading to measured energy gains of up to 0.55 MeV.

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title:
  Dynamic control of laser driven electron acceleration in a photonic structure using programmable optical pulses


date: 5 September, 2025
original_link: https://arxiv.org/abs/2509.07997
pdf_url: https://arxiv.org/pdf/2509.07997
site: arxiv
title: Learning-Based Planning for Improving Science Return of Earth Observation Satellites
created_at: 2025-09-12 17:19:50.898094
author:
  Abigail Breitfeld;Alberto Candela;Juan Delfa;Akseli Kangaslahti;Itai Zilberstein;Steve Chien;David Wettergreen

summary:
  Abstract:Earth observing satellites are powerful tools for collecting scientific information about our planet, however they have limitations: they cannot easily deviate from their orbital trajectories, their sensors have a limited field of view, and pointing and operating these sensors can take a large amount of the spacecraft's resources. It is important for these satellites to optimize the data they collect and include only the most important or informative measurements. Dynamic targeting is an emerging concept in which satellite resources and data from a lookahead instrument are used to intelligently reconfigure and point a primary instrument. Simulation studies have shown that dynamic targeting increases the amount of scientific information gathered versus conventional sampling strategies. In this work, we present two different learning-based approaches to dynamic targeting, using reinforcement and imitation learning, respectively. These learning methods build on a dynamic programming solution to plan a sequence of sampling locations. We evaluate our approaches against existing heuristic methods for dynamic targeting, showing the benefits of using learning for this application. Imitation learning performs on average 10.0\% better than the best heuristic method, while reinforcement learning performs on average 13.7\% better. We also show that both learning methods can be trained effectively with relatively small amounts of data.

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author: Patrick Kreidl
date: 9 September, 2025
original_link: https://arxiv.org/abs/2509.07840
pdf_url: https://arxiv.org/pdf/2509.07840
site: arxiv
title: Sensor Management in Multi-Stage Stochastic Control Problems with Imperfect State Information
created_at: 2025-09-12 17:19:50.898512
summary:
  Abstract:Technological advancements in miniaturization and wireless communications are yielding more affordable and versatile sensors and, in turn, more applications in which a network of sensors can be actively managed to best support overall decision-making objectives. We propose modeling the opportunity for sensor management within multi-stage stochastic control problems with imperfect state information. Such formulations inherently assume the state of the modeled environment cannot be accessed directly but instead the controller can observe only noisy measurements of the state and, therefore, at each decision stage some form of state estimation is required before a control is actuated. The notion of sensor management arises when the modeled controls not only affect the subsequent evolution of the state but can also affect the nature of future measurements and, hence, the quality of state estimates that drive future control decisions. In principle, the optimal strategy for any appropriately modeled multi-stage stochastic control problem with imperfect state information (with or without opportunity for sensor management) is the solution to a dynamic program; in practice, the computational requirements are typically prohibitive yet dynamic programming methods are still useful to guide the development of effective suboptimal strategies. In this spirit, we model the opportunity for sensor management within small-scale examples of two well-studied dynamic programming formulations, namely (1) the finite-state/finite-action Partially-Observable Markov Decision Process (PO-MDP) and (2) the Linear-Quadratic-Gaussian Regulator (LQGR). These examples admit solvable dynamic programs and confirm how the interplay between sensing and acting is a natural by-product of a dynamic programming solution.

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author: Muzaffar Habib;Adnan Maqsood;Adnan Fayyaz ud Din
date: 9 September, 2025
original_link: https://arxiv.org/abs/2509.07707
pdf_url: https://arxiv.org/pdf/2509.07707
site: arxiv
title: Fault Tolerant Control of a Quadcopter using Reinforcement Learning
created_at: 2025-09-12 17:19:50.898924
summary:
  Abstract:This study presents a novel reinforcement learning (RL)-based control framework aimed at enhancing the safety and robustness of the quadcopter, with a specific focus on resilience to in-flight one propeller failure. Addressing the critical need of a robust control strategy for maintaining a desired altitude for the quadcopter to safe the hardware and the payload in physical applications. The proposed framework investigates two RL methodologies Dynamic Programming (DP) and Deep Deterministic Policy Gradient (DDPG), to overcome the challenges posed by the rotor failure mechanism of the quadcopter. DP, a model-based approach, is leveraged for its convergence guarantees, despite high computational demands, whereas DDPG, a model-free technique, facilitates rapid computation but with constraints on solution duration. The research challenge arises from training RL algorithms on large dimensions and action domains. With modifications to the existing DP and DDPG algorithms, the controllers were trained not only to cater for large continuous state and action domain and also achieve a desired state after an inflight propeller failure. To verify the robustness of the proposed control framework, extensive simulations were conducted in a MATLAB environment across various initial conditions and underscoring its viability for mission-critical quadcopter applications. A comparative analysis was performed between both RL algorithms and their potential for applications in faulty aerial systems.

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author: Sungjun Eom;Gyunghoon Park
date: 9 September, 2025
original_link: https://arxiv.org/abs/2509.07546
pdf_url: https://arxiv.org/pdf/2509.07546
site: arxiv
created_at: 2025-09-12 17:19:50.899365
summary:
  Abstract:This work addresses an extended class of optimal control problems where a target for a system state has the form of an ellipsoid rather than a fixed, single point. As a computationally affordable method for resolving the extended problem, we present a revised version of the differential dynamic programming (DDP), termed the differential dynamic programming with ellipsoidal target set (ETS-DDP). To this end, the problem with an ellipsoidal target set is reformulated into an equivalent form with the orthogonal projection operator, yielding that the resulting cost functions turn out to be discontinuous at some points. As the DDP usually requires the differentiability of cost functions, in the ETS-DDP formulation we locally approximate the (nonsmooth) cost functions to smoothed ones near the path generated at the previous iteration, by utilizing the explicit form of the orthogonal projection operator. Moreover, a statistical inference method is also presented for designing the ellipsoidal target set, based on data on admissible target points collected by expert demonstrations. Via a simulation on autonomous parking of a vehicle, it is seen that the proposed ETS-DDP efficiently derives an admissible state trajectory while running much faster than the point-targeted DDP, at the expense of optimality.

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title:
  Differential Dynamic Programming for the Optimal Control Problem with an Ellipsoidal Target Set and Its Statistical Inference


date: 9 September, 2025
original_link: https://arxiv.org/abs/2509.07431
pdf_url: https://arxiv.org/pdf/2509.07431
site: arxiv
title: Network-accelerated Active Messages
created_at: 2025-09-12 17:19:50.899775
author:
  Md Ashfaqur Rahaman;Alireza Sanaee;Todd Thornley;Sebastiano Miano;Gianni Antichi;Brent E. Stephens;Ryan Stutsman

summary:
  Abstract:Remote Direct Memory Access (RDMA) improves host networking performance by eliminating software and server CPU involvement. However, RDMA has a limited set of operations, is difficult to program, and often requires multiple round trips to perform simple application operations. Programmable SmartNICs provide a different means to offload work from host CPUs to a NIC. This leaves applications with the complex choice of embedding logic as RPC handlers at servers, using RDMA's limited interface to access server structures via client-side logic, or running some logic on SmartNICs. The best choice varies between workloads and over time. To solve this dilemma, we present NAAM, network-accelerated active messages. NAAM applications specify small, portable eBPF functions associated with messages. Each message specifies what data it accesses using an RDMA-like interface. NAAM runs at various places in the network, including at clients, on server-attached SmartNICs, and server host CPU cores. Due to eBPF's portability, the code associated with a message can be run at any location. Hence, the NAAM runtime can dynamically steer any message to execute its associated logic wherever it makes the most sense. To demonstrate NAAM's flexibility, we built several applications, including the MICA hash table and lookups from a Cell-style B-tree. With an NVIDIA BlueField-2 SmartNIC and integrating its NIC-embedded switch, NAAM can run any of these operations on client, server, and NIC cores, shifting load in tens of milliseconds on server compute congestion. NAAM dynamically offloads up to 1.8 million MICA ops/s for YCSB-B and 750,000 Cell lookups/s from server CPUs. Finally, whereas iPipe, the state-of-the-art SmartNIC offload framework, only scales to 8 application offloads on BlueField-2, NAAM scales to hundreds of application offloads with minimal impact on tail latency due to eBPF's low overhead.

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author: Wei Liu;Tianchun Li;Mengshi Lu;Pengyi Shi
date: 9 September, 2025
original_link: https://arxiv.org/abs/2509.07387
pdf_url: https://arxiv.org/pdf/2509.07387
site: arxiv
title: Dynamic Redeployment of Nurses Across Hospitals: A Sample Robust Optimization Approach
created_at: 2025-09-12 17:19:50.900186
summary:
  Abstract:Problem definition: We study a workforce redeployment problem in hospital networks, where clinical staff, such as nurses, are temporarily reassigned from overstaffed to understaffed sites to address short-term imbalances. This practice of ``internal travel,'' which gained traction during the COVID-19 pandemic to tackle nurse shortages, presents new operational challenges that require tailored analytical support. Key requirements such as advance notice and short-term secondments must be incorporated. Moreover, in rapidly evolving environments, reliance on historical data leads to unreliable forecasts, limiting the effectiveness of traditional sample-based methods. Methodology: We formulate the problem as a stochastic dynamic program and incorporate demand uncertainty via a sample robust optimization (SRO) framework. Using linear decision rule approximation, we reformulate the problem as a tractable linear program. Results: We evaluate the impact of key network design components on system performance. Network connectivity has the largest effect in reducing the total cost, number of redeployments, and travel distance, but its benefits depend on aligning the secondment duration with the network structure. Full connectivity without proper secondments can be counterproductive. The SRO approach outperforms the traditional sample-average method in the presence of demand surges or under-forecasts by better anticipating emergency redeployments. Managerial implications: Internal travel programs offer a promising strategy to alleviate workforce shortages in healthcare systems. Our results highlight the importance of network design, aligning secondment durations with the network structure, and adopting planning methods that are robust to demand surges or inaccurate predictions.

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author: Andrew Kiruluta;Priscilla Burity
date: 6 September, 2025
original_link: https://arxiv.org/abs/2509.07017
pdf_url: https://arxiv.org/pdf/2509.07017
site: arxiv
created_at: 2025-09-12 17:19:50.900613
summary:
  Abstract:We introduce Spectral NSR, a fully spectral neuro-symbolic reasoning framework that embeds logical rules as spectral templates and performs inference directly in the graph spectral domain. By leveraging graph signal processing (GSP) and frequency-selective filters grounded in the Laplacian eigenstructure of knowledge graphs, the architecture unifies the interpretability of symbolic reasoning with the scalability and adaptability of spectral learning. Beyond the core formulation, we incorporate a comprehensive set of extensions, including dynamic graph and basis learning, rational and diffusion filters for sharper spectral selectivity, mixture-of-spectral-experts for modular specialization, proof-guided training with spectral curricula, and uncertainty quantification for calibrated confidence. Additional enhancements such as large language model coupling, co-spectral transfer alignment, adversarial robustness, efficient GPU kernels, generalized Laplacians, and causal interventions further expand the versatility of the framework.

  Empirical evaluation on state-of-the-art reasoning benchmarks such as ProofWriter and CLUTRR demonstrates that Spectral NSR achieves superior accuracy, faster inference, improved robustness to adversarial perturbations, and higher interpretability compared to leading baselines including transformers, message-passing neural networks, and neuro-symbolic logic programming systems. Spectral attribution and proof-band agreement analyses confirm that model decisions align closely with symbolic proof structures, while transfer experiments validate effective domain adaptation through co-spectral alignment. These results establish Spectral NSR as a scalable and principled foundation for the next generation of reasoning systems, offering transparency, robustness, and generalization beyond conventional approaches.

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title:
  From Eigenmodes to Proofs: Integrating Graph Spectral Operators with Symbolic Interpretable Reasoning


author: Hossein Rastgoftar
date: 8 September, 2025
original_link: https://arxiv.org/abs/2509.06758
pdf_url: https://arxiv.org/pdf/2509.06758
site: arxiv
title: Steering Opinion through Dynamic Stackelberg Optimization
created_at: 2025-09-12 17:19:50.901021
summary:
  Abstract:This paper employs the Friedkin-Johnsen (FJ) model to describe the dynamics of opinion evolution within a social network. Under the FJ framework, the society is divided into two subgroups that include stubborn agents and regular agents. The opinions of stubborn agents are not influenced by regular agents, whereas the opinions of regular agents evolve based on the opinions of their neighboring agents. By defining the origin as the desired collective opinion of the society, the objective of the paper is to minimize deviations from this desired opinion. To achieve this, a Stackelberg game is established between the stubborn and regular subgroups, where the opinion adjustments of the stubborn agents and the openness variables of regular agents serve as the decision variables. The proposed solution approach integrates quadratic programming and dynamic programming to optimize these decision variables at each discrete time step using forward and backward propagation.

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date: 8 September, 2025
original_link: https://arxiv.org/abs/2509.06668
pdf_url: https://arxiv.org/pdf/2509.06668
site: arxiv
parsed_summary: {"background": "", "contribution": "", "method": "", "objective": "", "results": ""}
title: Transient Observations with LST-1: Key Results and Future Prospects
created_at: 2025-09-12 17:19:50.901414
author:
  Monica Seglar-Arroyo;Alessio Berti;Alessandro Carosi;Gloria Maria Cicciari;Alice Donini;Armand Fiasson;Arnau Aguasca-Cabot;Mathieu de Bony;Pol Bordas;Marc Ribó;Edna Ruiz-Velasco;Fabian Schüssler

summary:
  Abstract:The recent detections of the afterglow phase of long gamma-ray bursts (lGRBs) at very high energies (VHE, >100 GeV) mark a significant advance in astrophysics of transient phenomena, offering deeper insights into the acceleration mechanisms, jet structure, and physical processes driving GRB emission. In the multi-messenger landscape, both high-energy neutrino and gravitational wave detections are providing new insights into the physics of extreme cosmic accelerators and highlighting the need for rapid and broadband follow-up observations. The Large-Sized Telescope (LST-1), the first telescope of the LST array, part of the Cherenkov Telescope Array Observatory (CTAO) North site, is particularly well-suited for real-time, rapid follow-up of transients. In this contribution, we present the latest achievements of the transient observational program with LST-1, which is now in advanced commissioning on La Palma, Canary Islands. We outline the observational strategies in place and describe the dynamic handling of events by the transient handler of LST-1 (e.g., its ability to handle poorly localised events, including gravitational waves, GRBs and neutrinos). We present the key results from transient observation campaigns conducted so far, discuss the lessons learned, and outline the promising prospects for the future LST-1+MAGIC combined transient program with fast response, via a Transient Handler.


author: Nalbantoğlu ÖU.
original_link: https://pubmed.ncbi.nlm.nih.gov/24170392/
site: pubmed
title: Dynamic programming.
created_at: 2025-09-12 17:19:50.901829
summary:
  Independent scoring of the aligned sections to determine the quality of biological sequence alignments enables recursive definitions of the overall alignment score. This property is not only biologically meaningful but it also provides the opportunity to find the optimal alignments using dynamic programming-based algorithms. Dynamic programming is an efficient problem solving technique for a class of problems that can be solved by dividing into overlapping subproblems. Pairwise sequence alignment techniques such as Needleman-Wunsch and Smith-Waterman algorithms are applications of dynamic programming on pairwise sequence alignment problems. These algorithms offer polynomial time and space solutions. In this chapter, we introduce the basic dynamic programming solutions for global, semi-global, and local alignment problems. Algorithmic improvements offering quadratic-time and linear-space programs and approximate solutions with space-reduction and seeding heuristics are discussed. We finally introduce the application of these techniques on multiple sequence alignment briefly.

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author: Ungru K, Jiang X.
original_link: https://pubmed.ncbi.nlm.nih.gov/28289536/
pdf_url: https://pmc.ncbi.nlm.nih.gov/articles/PMC5338725/pdf/main.pdf
site: pubmed
title: Dynamic Programming Based Segmentation in Biomedical Imaging.
created_at: 2025-09-12 17:19:50.902248
summary:
  Many applications in biomedical imaging have a demand on automatic detection of lines, contours, or boundaries of bones, organs, vessels, and cells. Aim is to support expert decisions in interactive applications or to include it as part of a processing pipeline for automatic image analysis. Biomedical images often suffer from noisy data and fuzzy edges. Therefore, there is a need for robust methods for contour and line detection. Dynamic programming is a popular technique that satisfies these requirements in many ways. This work gives a brief overview over approaches and applications that utilize dynamic programming to solve problems in the challenging field of biomedical imaging.

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author: Son J, Gluza M, Takagi R, Ng NHY.
original_link: https://pubmed.ncbi.nlm.nih.gov/40408699/
site: pubmed
title: Quantum Dynamic Programming.
created_at: 2025-09-12 17:19:50.902652
summary:
  We introduce a quantum extension of dynamic programming, a fundamental computational method that efficiently solves recursive problems using memory. Our innovation lies in showing how to coherently generate recursion step unitaries by using memorized intermediate quantum states. Quantum dynamic programming achieves an exponential reduction in circuit depth for a broad class of fixed-point quantum recursions, though this comes at the cost of increased circuit width. Interestingly, the trade-off becomes more favorable when the initial state is pure. By hybridizing our approach with a conventional memoryless one, we can flexibly balance circuit depth and width to optimize performance on quantum devices with fixed hardware constraints. Finally, we showcase applications of quantum dynamic programming to several quantum recursions, including a variant of Grover's search, quantum imaginary-time evolution, and a new protocol for obliviously preparing a quantum state in its Schmidt basis.

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author: Lin D, Xue S, Liu D, Liang M, Wang Y.
original_link: https://pubmed.ncbi.nlm.nih.gov/37673023/
site: pubmed
title: Adaptive dynamic programming-based hierarchical decision-making of non-affine systems.
created_at: 2025-09-12 17:19:50.903086
summary:
  In this paper, the problem of multiplayer hierarchical decision-making problem for non-affine systems is solved by adaptive dynamic programming. Firstly, the control dynamics are obtained according to the theory of dynamic feedback and combined with the original system dynamics to construct the affine augmented system. Thus, the non-affine multiplayer system is transformed into a general affine form. Then, the hierarchical decision problem is modeled as a Stackelberg game. In the Stackelberg game, the leader makes a decision based on the information of all followers, whereas the followers do not know each other's information and only obtain their optimal control strategy based on the leader's decision. Then, the augmented system is reconstructed by a neural network (NN) using input-output data. Moreover, a single critic NN is used to approximate the value function to obtain the optimal control strategy for each player. An extra term added to the weight update law makes the initial admissible control law no longer needed. According to the Lyapunov theory, the state of the system and the error of the weights of the NN are both uniformly ultimately bounded. Finally, the feasibility and validity of the algorithm are confirmed by simulation.

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author: Gratacos G, Chakrabarti A, Ju T.
original_link: https://pubmed.ncbi.nlm.nih.gov/37505999/
site: pubmed
title: Tree Recovery by Dynamic Programming.
created_at: 2025-09-12 17:19:50.903501
summary:
  Tree-like structures are common, naturally occurring objects that are of interest to many fields of study, such as plant science and biomedicine. Analysis of these structures is typically based on skeletons extracted from captured data, which often contain spurious cycles that need to be removed. We propose a dynamic programming algorithm for solving the NP-hard tree recovery problem formulated by (Estrada et al. 2015), which seeks a least-cost partitioning of the graph nodes that yields a directed tree. Our algorithm finds the optimal solution by iteratively contracting the graph via node-merging until the problem can be trivially solved. By carefully designing the merging sequence, our algorithm can efficiently recover optimal trees for many real-world data where (Estrada et al. 2015) only produces sub-optimal solutions. We also propose an approximate variant of dynamic programming using beam search, which can process graphs containing thousands of cycles with significantly improved optimality and efficiency compared with (Estrada et al. 2015).

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author: Voß B.
original_link: https://pubmed.ncbi.nlm.nih.gov/38780730/
site: pubmed
title: Classified Dynamic Programming in RNA Structure Analysis.
created_at: 2025-09-12 17:19:50.903907
summary:
  Analysis of the folding space of RNA generally suffers from its exponential size. With classified Dynamic Programming algorithms, it is possible to alleviate this burden and to analyse the folding space of RNA in great depth. Key to classified DP is that the search space is partitioned into classes based on an on-the-fly computed feature. A class-wise evaluation is then used to compute class-wide properties, such as the lowest free energy structure for each class, or aggregate properties, such as the class' probability. In this paper we describe the well-known shape and hishape abstraction of RNA structures, their power to help better understand RNA function and related methods that are based on these abstractions.

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author: Lv Z, Chen Y, Di R, Wang H, Sun X, He C, Li X.
original_link: https://pubmed.ncbi.nlm.nih.gov/37420374/
pdf_url: https://pmc.ncbi.nlm.nih.gov/articles/PMC9601758/pdf/entropy-24-01354.pdf
site: pubmed
created_at: 2025-09-12 17:19:50.904319
summary:
  The Bayesian Network (BN) structure learning algorithm based on dynamic programming can obtain global optimal solutions. However, when the sample cannot fully contain the information of the real structure, especially when the sample size is small, the obtained structure is inaccurate. Therefore, this paper studies the planning mode and connotation of dynamic programming, restricts its process with edge and path constraints, and proposes a dynamic programming BN structure learning algorithm with double constraints under small sample conditions. The algorithm uses double constraints to limit the planning process of dynamic programming and reduces the planning space. Then, it uses double constraints to limit the selection of the optimal parent node to ensure that the optimal structure conforms to prior knowledge. Finally, the integrating prior-knowledge method and the non-integrating prior-knowledge method are simulated and compared. The simulation results verify the effectiveness of the method proposed and prove that the integrating prior knowledge can significantly improve the efficiency and accuracy of BN structure learning.

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title:
  Dynamic Programming BN Structure Learning Algorithm Integrating Double Constraints under Small Sample Condition.


author: Xing X, Chang DE.
original_link: https://pubmed.ncbi.nlm.nih.gov/34451052/
pdf_url: https://pmc.ncbi.nlm.nih.gov/articles/PMC8402451/pdf/sensors-21-05609.pdf
site: pubmed
title: The Adaptive Dynamic Programming Toolbox.
created_at: 2025-09-12 17:19:50.904738
summary:
  The paper develops the adaptive dynamic programming toolbox (ADPT), which is a MATLAB-based software package and computationally solves optimal control problems for continuous-time control-affine systems. The ADPT produces approximate optimal feedback controls by employing the adaptive dynamic programming technique and solving the Hamilton-Jacobi-Bellman equation approximately. A novel implementation method is derived to optimize the memory consumption by the ADPT throughout its execution. The ADPT supports two working modes: model-based mode and model-free mode. In the former mode, the ADPT computes optimal feedback controls provided the system dynamics. In the latter mode, optimal feedback controls are generated from the measurements of system trajectories, without the requirement of knowledge of the system model. Multiple setting options are provided in the ADPT, such that various customized circumstances can be accommodated. Compared to other popular software toolboxes for optimal control, the ADPT features computational precision and time efficiency, which is illustrated with its applications to a highly non-linear satellite attitude control problem.

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author: Han Y, Cameron JN, Wang L, Pham H, Beavis WD.
original_link: https://pubmed.ncbi.nlm.nih.gov/34220873/
pdf_url: https://pmc.ncbi.nlm.nih.gov/articles/PMC8253225/pdf/fpls-12-544854.pdf
site: pubmed
title: Dynamic Programming for Resource Allocation in Multi-Allelic Trait Introgression.
created_at: 2025-09-12 17:19:50.905144
summary:
  Trait introgression is a complex process that plant breeders use to introduce desirable alleles from one variety or species to another. Two of the major types of decisions that must be made during this sophisticated and uncertain workflow are: parental selection and resource allocation. We formulated the trait introgression problem as an engineering process and proposed a Markov Decision Processes (MDP) model to optimize the resource allocation procedure. The efficiency of the MDP model was compared with static resource allocation strategies and their trade-offs among budget, deadline, and probability of success are demonstrated. Simulation results suggest that dynamic resource allocation strategies from the MDP model significantly improve the efficiency of the trait introgression by allocating the right amount of resources according to the genetic outcome of previous generations.

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author: Holmes I, Durbin R.
original_link: https://pubmed.ncbi.nlm.nih.gov/9773345/
site: pubmed
title: Dynamic programming alignment accuracy.
created_at: 2025-09-12 17:19:50.905552
summary:
  Algorithms for generating alignments of biological sequences have inherent statistical limitations when it comes to the accuracy of the alignments they produce. Using simulations, we measure the accuracy of the standard global dynamic programming method and show that it can be reasonably well modelled by an "edge wander" approximation to the distribution of the optimal scoring path around the correct path in the vicinity of a gap. We also give a table from which accuracy values can be predicted for commonly used scoring schemes and sequence divergences (the PAM and BLOSUM series). Finally we describe how to calculate the expected accuracy of a given alignment, and show how this can be used to construct an optimal accuracy alignment algorithm which generates significantly more accurate alignments than standard dynamic programming methods in simulated experiments.

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author: 张錋;张道娟;陈凯;赵宇飞;张英杰
date: 2025-09-11 11:01
keywords: 对抗性防御;;检索增强分类;;自然语言处理;;模型鲁棒性;;KNN检索;;表征学习;
source: 计算机科学
site: 知网
title: 基于检索增强分类与解耦表示的NLP对抗鲁棒性提升方法
created_at: 2025-09-12 18:17:10.413804
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kcnPyYk9idc8wCw691v7B4V3EbEF5ocd_9_fhX7TyjARCfJDAkWJlxiXpbwSN9qo1cJVu75NzND8chPRiyGZlca7rGYQtoGcqPZ2vuW54d5soeyUAEAtcBp7K7hbWt31SV1-GpvZWQp5s2-hcr1z2KRR97FLHm5CzNFTgjy39epbw==&uniplatform=NZKPT&language=CHS

summary:
  虽然自然语言处理（NLP）模型在各类文本分类任务中表现优异，但面对对抗性攻击时依然存在较大脆弱性。为应对这一问题，本文提出了一种创新性的检索增强分类方法，有效提升模型在对抗环境下的鲁棒性。该方法引入了k-最近邻（KNN）检索机制，将模型自身的标签预测结果与检索到的相似样本标签分布相结合，使模型在遭受攻击时能做出更为稳健的判断。我们的一大创新在于将分类与检索所用的表示空间分开设计，从而避免因共享表示带来的性能下降和训练不稳定。通过在多种基准数据集和多样化对抗攻击场景下的实验，我们的方法显著提升了模型的鲁棒性——在对抗攻击下，准确率下降幅度减少了 30-40 个百分点，并且即使在强烈攻击下依然能够保持较为稳定的表现。大量实验进一步验证了该方法的有效性，表明检索增强分类和解耦表示对于构建更可靠的系统具有重要意义。

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author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-12 18:17:10.416205
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCGRlcGFvaHJz

summary:
  软件开发者在编写代码时,常常会参考项目中实现了相似功能的代码.代码生成模型在生成代码时也具有类似特点,会以输入中给出的代码上下文信息作为参考.基于检索增强的代码补全技术与这一思想类似,该技术从检索库中检索到外部代码作为额外信息,对生成模型起到提示的作用,从而生成目标代码.现有的基于检索增强的代码补全方法将输入代码和检索结果直接拼接到一起作为生成模型的输入,这种方法带来了一个风险,即检索到的代码片段可能并不能对模型起到提示作用,反而有可能会误导模型,导致生成的代码结果不准确.此外,由于无论检索到的外部代码是否与输入代码完全相关,都会被与输入代码拼接起来输入到模型,这导致该方法的效果在很大程度上依赖于代码检索阶段的准确性.如果检索阶段不能返回可用的代码片段,那么后续的代码补全效果可能也会受到影响.首先,针对现有的代码补全方法中的检索增强策略进行了经验研究,通过定性和定量实验分析检索增强的各个阶段对于代码补全效果的影响,在经验研究中重点识别了代码粒度、代码检索方法、代码后处理方法这 3 种影响检索增强效果的因素.接着,基于经验研究的结论设计改进方法,提出一种通过分阶段优化代码检索策略来改进检索增强的代码补全方法MAGIC(multi-stage optimization for retrieval augmented code completion),设计了代码切分、二次检索精排、模板提示生成等改进策略,可以有效地提升检索增强对代码补全模型的辅助生成作用,并减少模型在代码生成阶段受到的噪声干扰,提升生成代码的质量.最后,在Java代码数据集上的实验结果表明:与现有的基于检索增强的代码补全方法相比,该方法在编辑相似度和完全匹配指标上分别提升了 6.76%和7.81%.与 6B参数量的代码大模型相比,该方法能够在节省 94.5%的显存和 73.8%的推理时间的前提下,在编辑相似度和完全匹配指标上分别提升5.62%和4.66%.

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author: 高辉;陈历泉;鲁工圆
keywords: 检索增强生成;本地知识库;决策;大语言模型;高铁应急调度处置方案
source: 铁道运输与经济
site: 维普
title: 高铁应急调度处置方案的大语言模型检索增强生成方法
created_at: 2025-09-12 18:17:10.416670
original_link:
  https://www.cqvip.com/doc/journal/3507498426?sign=ce6d161fa3c7518f94d0af58dbb14951f34fca33bdbf171b504040c8fc509a9e&expireTime=1789208058028&resourceId=3507498426

summary:
  既有的高速铁路应急调度处置方案决策方法,依赖铁路局调度所的高速铁路行车调度台,由列车调度员或成立专门小组根据规章制度和现场情况选择方案,通过与现场交互解决问题。为提高决策效率,提出高铁应急调度处置方案的大语言模型检索增强生成方法。首先,分析决策流程,提出高铁应急调度处置方案的大语言模型检索增强生成问题;其次,基于高速铁路列车调度员应急处置指导书,建立本地知识库;然后,构建大语言模型提示词模板,设计本地知识库的检索方法;最后,提出高铁应急调度处置方案的修正方法。实验结果显示,该方法在BLEU、ROUGE-1、ROUGE-2、ROUGE-L指标上达到了0.9122,0.9878,0.9786,0.9878,且纠错正确率达到了89.77%。结果表明,该方法不仅在生成高质量长文本方面表现出显著的有效性,还具备文本纠错能力。同时,在小参数规模的大语言模型chatglm2-6b下,该方法在相同指标上达到了0.8623,0.9579,0.9360,0.9559,依然保持了较高性能,进一步验证了其在小参数大语言模型下的有效性。

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date: 2025
original_link: https://ieeexplore.ieee.org/document/11079738/
site: ieeeXplore
title: A Simple Guide to Retrieval Augmented Generation
created_at: 2025-09-12 18:17:10.417098
summary:
  <b>Everything you need to know about Retrieval Augmented Generation in one human-friendly guide.</b><br><br> Retrieval Augmented Generation—or RAG—enhances an LLM’s available data by adding context from an external knowledge base, so it can answer accurately about proprietary content, recent information, and even live conversations. RAG is powerful, and with <i>A Simple Guide to Retrieval Augmented Generation</i>, it’s also easy to understand and implement!<br><br> In <i>A Simple Guide to Retrieval Augmented Generation</i> you’ll learn:<br><br> <ul> <li>The components of a RAG system</li> <li>How to create a RAG knowledge base</li> <li>The indexing and generation pipeline</li> <li>Evaluating a RAG system</li> <li>Advanced RAG strategies</li> <li>RAG tools, technologies, and frameworks</li> </ul><br> <i>A Simple Guide to Retrieval Augmented Generation</i> gives an easy, yet comprehensive, introduction to RAG for AI beginners. You’ll go from basic RAG that uses indexing and generation pipelines, to modular RAG and multimodal data from images, spreadsheets, and more.</br></br></br></br></br></br></br>

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author: Zakaria El Kassimi;Fares Fourati;Mohamed-Slim Alouini
date: 11 September, 2025
original_link: https://arxiv.org/abs/2509.09651
site: arxiv
title: Retrieval-Augmented Generation for Reliable Interpretation of Radio Regulations
created_at: 2025-09-12 18:17:10.417540
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original_link: https://pubmed.ncbi.nlm.nih.gov/38343631/
pdf_url: https://pmc.ncbi.nlm.nih.gov/articles/PMC10857783/pdf/nihms-1962112.pdf
site: pubmed
title: Almanac - Retrieval-Augmented Language Models for Clinical Medicine.
created_at: 2025-09-12 18:17:10.417955
author:
  Zakka C, Shad R, Chaurasia A, Dalal AR, Kim JL, Moor M, Fong R, Phillips C, Alexander K, Ashley E, Boyd J, Boyd K, Hirsch K, Langlotz C, Lee R, Melia J, Nelson J, Sallam K, Tullis S, Vogelsong MA, Cunningham JP, Hiesinger W.

summary:
  Background: Large language models (LLMs) have recently shown impressive zero-shot capabilities, whereby they can use auxiliary data, without the availability of task-specific training examples, to complete a variety of natural language tasks, such as summarization, dialogue generation, and question answering. However, despite many promising applications of LLMs in clinical medicine, adoption of these models has been limited by their tendency to generate incorrect and sometimes even harmful statements.

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author: 张錋;张道娟;陈凯;赵宇飞;张英杰
date: 2025-09-11 11:01
keywords: 对抗性防御;;检索增强分类;;自然语言处理;;模型鲁棒性;;KNN检索;;表征学习;
source: 计算机科学
site: 知网
title: 基于检索增强分类与解耦表示的NLP对抗鲁棒性提升方法
created_at: 2025-09-12 18:25:00.128063
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kc8ICoK3ks0X737EKgLOn-AUPREjgqGwEBfLQ-Ca9C9KCo3CLrH92jsCDIpNake-XiDmVuig3hlNNy87J4yXnNGHTXU5dAHLOcP-6rHtwMwFsxOEtNGxTynrQrJ5yx-rsboWwaE7L22N6XXsSqTzJSSYDnFZWJJCGW8pCxD-9111w==&uniplatform=NZKPT&language=CHS

summary:
  虽然自然语言处理（NLP）模型在各类文本分类任务中表现优异，但面对对抗性攻击时依然存在较大脆弱性。为应对这一问题，本文提出了一种创新性的检索增强分类方法，有效提升模型在对抗环境下的鲁棒性。该方法引入了k-最近邻（KNN）检索机制，将模型自身的标签预测结果与检索到的相似样本标签分布相结合，使模型在遭受攻击时能做出更为稳健的判断。我们的一大创新在于将分类与检索所用的表示空间分开设计，从而避免因共享表示带来的性能下降和训练不稳定。通过在多种基准数据集和多样化对抗攻击场景下的实验，我们的方法显著提升了模型的鲁棒性——在对抗攻击下，准确率下降幅度减少了 30-40 个百分点，并且即使在强烈攻击下依然能够保持较为稳定的表现。大量实验进一步验证了该方法的有效性，表明检索增强分类和解耦表示对于构建更可靠的系统具有重要意义。

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author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-12 18:25:00.130693
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCG12cXBuNm9o

summary:
  软件开发者在编写代码时,常常会参考项目中实现了相似功能的代码.代码生成模型在生成代码时也具有类似特点,会以输入中给出的代码上下文信息作为参考.基于检索增强的代码补全技术与这一思想类似,该技术从检索库中检索到外部代码作为额外信息,对生成模型起到提示的作用,从而生成目标代码.现有的基于检索增强的代码补全方法将输入代码和检索结果直接拼接到一起作为生成模型的输入,这种方法带来了一个风险,即检索到的代码片段可能并不能对模型起到提示作用,反而有可能会误导模型,导致生成的代码结果不准确.此外,由于无论检索到的外部代码是否与输入代码完全相关,都会被与输入代码拼接起来输入到模型,这导致该方法的效果在很大程度上依赖于代码检索阶段的准确性.如果检索阶段不能返回可用的代码片段,那么后续的代码补全效果可能也会受到影响.首先,针对现有的代码补全方法中的检索增强策略进行了经验研究,通过定性和定量实验分析检索增强的各个阶段对于代码补全效果的影响,在经验研究中重点识别了代码粒度、代码检索方法、代码后处理方法这 3 种影响检索增强效果的因素.接着,基于经验研究的结论设计改进方法,提出一种通过分阶段优化代码检索策略来改进检索增强的代码补全方法MAGIC(multi-stage optimization for retrieval augmented code completion),设计了代码切分、二次检索精排、模板提示生成等改进策略,可以有效地提升检索增强对代码补全模型的辅助生成作用,并减少模型在代码生成阶段受到的噪声干扰,提升生成代码的质量.最后,在Java代码数据集上的实验结果表明:与现有的基于检索增强的代码补全方法相比,该方法在编辑相似度和完全匹配指标上分别提升了 6.76%和7.81%.与 6B参数量的代码大模型相比,该方法能够在节省 94.5%的显存和 73.8%的推理时间的前提下,在编辑相似度和完全匹配指标上分别提升5.62%和4.66%.

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author: 高辉;陈历泉;鲁工圆
keywords: 检索增强生成;本地知识库;决策;大语言模型;高铁应急调度处置方案
source: 铁道运输与经济
site: 维普
title: 高铁应急调度处置方案的大语言模型检索增强生成方法
created_at: 2025-09-12 18:25:00.131178
original_link:
  https://www.cqvip.com/doc/journal/3507498426?sign=054fdd7c20d4ddc120ebfff16eebf6b5c5fec5da00fe2ac1a7d26d2ef6cbd887&expireTime=1789208519658&resourceId=3507498426

summary:
  既有的高速铁路应急调度处置方案决策方法,依赖铁路局调度所的高速铁路行车调度台,由列车调度员或成立专门小组根据规章制度和现场情况选择方案,通过与现场交互解决问题。为提高决策效率,提出高铁应急调度处置方案的大语言模型检索增强生成方法。首先,分析决策流程,提出高铁应急调度处置方案的大语言模型检索增强生成问题;其次,基于高速铁路列车调度员应急处置指导书,建立本地知识库;然后,构建大语言模型提示词模板,设计本地知识库的检索方法;最后,提出高铁应急调度处置方案的修正方法。实验结果显示,该方法在BLEU、ROUGE-1、ROUGE-2、ROUGE-L指标上达到了0.9122,0.9878,0.9786,0.9878,且纠错正确率达到了89.77%。结果表明,该方法不仅在生成高质量长文本方面表现出显著的有效性,还具备文本纠错能力。同时,在小参数规模的大语言模型chatglm2-6b下,该方法在相同指标上达到了0.8623,0.9579,0.9360,0.9559,依然保持了较高性能,进一步验证了其在小参数大语言模型下的有效性。

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author: Monica Palla;K. Renu
date: 2025
original_link: https://ieeexplore.ieee.org/document/11013429/
site: ieeeXplore
created_at: 2025-09-12 18:25:00.131610
summary:
  A large collection of digital images has resulted from the quick growth of multimedia technologies, making effective retrieval a difficult undertaking. Improving retrieval performance, especially in benchmark datasets like the Wang dataset, requires efficient image feature extraction and representation. In this study, a Content-Based Image Retrieval (CBIR) system uses deep learning techniques to enhance the connection between low-level features and high-level semantic representations. Traditional methods require manual selection and extraction of features, which is time-consuming and may not capture relevant information from all the images. The primary objective of this study is to introduce a custom Convolutional Neural Network (CNN) that improves retrieval precision by enhancing feature extraction and addressing the semantic gap. Furthermore, data augmentation is added to make the CBIR system rotation-invariant, which can handle variations in image orientations. In this research work, the Wang dataset is used for experimental evaluation. The system retrieves similar images by comparing features from query images and dataset images based on similarity measurement using Euclidean distance. The performance of the system is evaluated by using Precision at k (P@k), Average Precision at k (AP@k), and mean Average Precision at K (mAP@k) across all classes in the wang dataset. Evaluation results show that the proposed Custom CNN-based CBIR system achieves mAP@20 at 97.8<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> and P@20 at 96.5%, which is high performance compared to the existing methods. This approach has potential applications in real-world domains like traffic surveillance, face recognition, wildlife conservation, and architectural design, where CBIR plays an important role.

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title:
  A Content-Based Image Retrieval System Using Custom Convolutional Neural Network for Enhanced Image Retrieval on the Wang Dataset


author: Guo Y, Qiu W, Leroy G, Wang S, Cohen T.
original_link: https://pubmed.ncbi.nlm.nih.gov/38163514/
pdf_url: https://pmc.ncbi.nlm.nih.gov/articles/PMC10874606/pdf/nihms-1961161.pdf
site: pubmed
title: Retrieval augmentation of large language models for lay language generation.
created_at: 2025-09-12 18:25:00.132302
summary:
  The complex linguistic structures and specialized terminology of expert-authored content limit the accessibility of biomedical literature to the general public. Automated methods have the potential to render this literature more interpretable to readers with different educational backgrounds. Prior work has framed such lay language generation as a summarization or simplification task. However, adapting biomedical text for the lay public includes the additional and distinct task of background explanation: adding external content in the form of definitions, motivation, or examples to enhance comprehensibility. This task is especially challenging because the source document may not include the required background knowledge. Furthermore, background explanation capabilities have yet to be formally evaluated, and little is known about how best to enhance them. To address this problem, we introduce Retrieval-Augmented Lay Language (RALL) generation, which intuitively fits the need for external knowledge beyond that in expert-authored source documents. In addition, we introduce CELLS, the largest (63k pairs) and broadest-ranging (12 journals) parallel corpus for lay language generation. To evaluate RALL, we augmented state-of-the-art text generation models with information retrieval of either term definitions from the UMLS and Wikipedia, or embeddings of explanations from Wikipedia documents. Of these, embedding-based RALL models improved summary quality and simplicity while maintaining factual correctness, suggesting that Wikipedia is a helpful source for background explanation in this context. We also evaluated the ability of both an open-source Large Language Model (Llama 2) and a closed-source Large Language Model (GPT-4) in background explanation, with and without retrieval augmentation. Results indicate that these LLMs can generate simplified content, but that the summary quality is not ideal. Taken together, this work presents the first comprehensive study of background explanation for lay language generation, paving the path for disseminating scientific knowledge to a broader audience. Our code and data are publicly available at: https://github.com/LinguisticAnomalies/pls_retrieval.

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author: 张錋;张道娟;陈凯;赵宇飞;张英杰
date: 2025-09-11 11:01
keywords: 对抗性防御;;检索增强分类;;自然语言处理;;模型鲁棒性;;KNN检索;;表征学习;
source: 计算机科学
site: 知网
title: 基于检索增强分类与解耦表示的NLP对抗鲁棒性提升方法
created_at: 2025-09-12 18:31:27.307892
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kcRRG2U23OU3JQLCJBlrpiOwNVP2lnTY_z_1pkaBcMCbFW_unMNuz07ZrsqWSsy6P_te2co6twlAPxddc1k6UB0nyTgoPRmn1N9tOBeL6e8zCotNh-5e7BNsQeKBexCDqQUUaiCMEn-OJnEpTNL_iVSRtO9K58zGa7xs-Jn5goWog==&uniplatform=NZKPT&language=CHS

summary:
  虽然自然语言处理（NLP）模型在各类文本分类任务中表现优异，但面对对抗性攻击时依然存在较大脆弱性。为应对这一问题，本文提出了一种创新性的检索增强分类方法，有效提升模型在对抗环境下的鲁棒性。该方法引入了k-最近邻（KNN）检索机制，将模型自身的标签预测结果与检索到的相似样本标签分布相结合，使模型在遭受攻击时能做出更为稳健的判断。我们的一大创新在于将分类与检索所用的表示空间分开设计，从而避免因共享表示带来的性能下降和训练不稳定。通过在多种基准数据集和多样化对抗攻击场景下的实验，我们的方法显著提升了模型的鲁棒性——在对抗攻击下，准确率下降幅度减少了 30-40 个百分点，并且即使在强烈攻击下依然能够保持较为稳定的表现。大量实验进一步验证了该方法的有效性，表明检索增强分类和解耦表示对于构建更可靠的系统具有重要意义。

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author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-12 18:31:27.310532
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCGxxMzY2OTM4

summary:
  软件开发者在编写代码时,常常会参考项目中实现了相似功能的代码.代码生成模型在生成代码时也具有类似特点,会以输入中给出的代码上下文信息作为参考.基于检索增强的代码补全技术与这一思想类似,该技术从检索库中检索到外部代码作为额外信息,对生成模型起到提示的作用,从而生成目标代码.现有的基于检索增强的代码补全方法将输入代码和检索结果直接拼接到一起作为生成模型的输入,这种方法带来了一个风险,即检索到的代码片段可能并不能对模型起到提示作用,反而有可能会误导模型,导致生成的代码结果不准确.此外,由于无论检索到的外部代码是否与输入代码完全相关,都会被与输入代码拼接起来输入到模型,这导致该方法的效果在很大程度上依赖于代码检索阶段的准确性.如果检索阶段不能返回可用的代码片段,那么后续的代码补全效果可能也会受到影响.首先,针对现有的代码补全方法中的检索增强策略进行了经验研究,通过定性和定量实验分析检索增强的各个阶段对于代码补全效果的影响,在经验研究中重点识别了代码粒度、代码检索方法、代码后处理方法这 3 种影响检索增强效果的因素.接着,基于经验研究的结论设计改进方法,提出一种通过分阶段优化代码检索策略来改进检索增强的代码补全方法MAGIC(multi-stage optimization for retrieval augmented code completion),设计了代码切分、二次检索精排、模板提示生成等改进策略,可以有效地提升检索增强对代码补全模型的辅助生成作用,并减少模型在代码生成阶段受到的噪声干扰,提升生成代码的质量.最后,在Java代码数据集上的实验结果表明:与现有的基于检索增强的代码补全方法相比,该方法在编辑相似度和完全匹配指标上分别提升了 6.76%和7.81%.与 6B参数量的代码大模型相比,该方法能够在节省 94.5%的显存和 73.8%的推理时间的前提下,在编辑相似度和完全匹配指标上分别提升5.62%和4.66%.

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author: 高辉;陈历泉;鲁工圆
keywords: 检索增强生成;本地知识库;决策;大语言模型;高铁应急调度处置方案
source: 铁道运输与经济
site: 维普
title: 高铁应急调度处置方案的大语言模型检索增强生成方法
created_at: 2025-09-12 18:31:27.312720
original_link:
  https://www.cqvip.com/doc/journal/3507498426?sign=533ba2ed0162a34784ad68cc13dd5f9e8935d1ada16898235be57205620f6b79&expireTime=1789209032249&resourceId=3507498426

summary:
  既有的高速铁路应急调度处置方案决策方法,依赖铁路局调度所的高速铁路行车调度台,由列车调度员或成立专门小组根据规章制度和现场情况选择方案,通过与现场交互解决问题。为提高决策效率,提出高铁应急调度处置方案的大语言模型检索增强生成方法。首先,分析决策流程,提出高铁应急调度处置方案的大语言模型检索增强生成问题;其次,基于高速铁路列车调度员应急处置指导书,建立本地知识库;然后,构建大语言模型提示词模板,设计本地知识库的检索方法;最后,提出高铁应急调度处置方案的修正方法。实验结果显示,该方法在BLEU、ROUGE-1、ROUGE-2、ROUGE-L指标上达到了0.9122,0.9878,0.9786,0.9878,且纠错正确率达到了89.77%。结果表明,该方法不仅在生成高质量长文本方面表现出显著的有效性,还具备文本纠错能力。同时,在小参数规模的大语言模型chatglm2-6b下,该方法在相同指标上达到了0.8623,0.9579,0.9360,0.9559,依然保持了较高性能,进一步验证了其在小参数大语言模型下的有效性。

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author: 金哲;邹健;李逍;吕嘉欣;胡中旭
date: 2025-08-28
keywords: 大语言模型;;检索增强生成;;“幻觉”问题;;医学信息检索;
source: 药物流行病学杂志
site: 知网
title: 检索增强生成技术在医学人工智能中的应用与前沿探索
created_at: 2025-09-12 18:32:54.756366
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kfnsJvp1qcKZryIcCJhAGTUImWugsIUYGIVcvMkGwS1Fxbn6IWxbYvmpjIxWj6QZlcwbKz4Y7SukbPtKbkuEEUKLz6cPx_YzdyLy_K9iL3KZbjoezPUzsRdQcmOMj4IQsWt9O0hazkYdvg1cZt-XJAsrBBploYnwBRtiqKUYO_tmw==&uniplatform=NZKPT&language=CHS

summary:
  随着大语言模型（LLM）的蓬勃兴起，深度学习的自然语言生成能力在医学领域展现出了显著价值。然而模型参数的“封闭性”易导致其产生“幻觉”，难以对最新知识作出准确回答，且推理过程缺乏透明度与溯源。检索增强生成（RAG）技术通过在生成阶段主动连接外部文献数据库、知识图谱等信息源，大幅降低了LLM对过时训练数据的依赖，并在回答中引入可验证的证据和实时更新的知识。在医学领域，RAG技术有效解决了文献检索与临床决策支持中的高准确度与可追溯性需求，广泛应用于新药研发、药物警戒、罕见病诊疗等方面。结合强化学习、多模态处理与合规隐私保护等新兴技术，RAG技术正朝着更加开放、高度定制化的方向演进，为医学信息检索与辅助决策提供了全新的智能化解决方案。

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author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-12 18:32:54.757076
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCDM2YnhkYjM4

summary:
[cell repeats an earlier one in this file: 822 characters]

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  {"background": "\u5728\u4ee3\u7801\u8865\u5168\u4efb\u52a1\u4e2d\uff0c\u5f00\u53d1\u8005\u548c\u4ee3\u7801\u751f\u6210\u6a21\u578b\u5e38\u5e38\u501f\u52a9\u9879\u76ee\u5185\u76f8\u4f3c\u529f\u80fd\u4ee3\u7801\u4f5c\u4e3a\u53c2\u8003\u3002\u8fd1\u5e74\u6765\uff0c\u68c0\u7d22\u589e\u5f3a\u7b56\u7565\u901a\u8fc7\u5f15\u5165\u5916\u90e8\u68c0\u7d22\u4ee3\u7801\u4e3a\u751f\u6210\u6a21\u578b\u63d0\u4f9b\u989d\u5916\u4fe1\u606f\uff0c\u4f46\u5f53\u524d\u65b9\u6cd5\u7b80\u5355\u62fc\u63a5\u68c0\u7d22\u7ed3\u679c\u548c\u8f93\u5165\u4ee3\u7801\uff0c\u5b58\u5728\u68c0\u7d22\u7247\u6bb5\u5e72\u6270\u6a21\u578b\u3001\u5f71\u54cd\u4ee3\u7801\u8d28\u91cf\u7b49\u95ee\u9898\uff0c\u5bf9\u68c0\u7d22\u51c6\u786e\u6027\u4f9d\u8d56\u8f83\u9ad8\u3002", "contribution": "\u8bba\u6587\u6df1\u5165\u5206\u6790\u4e86\u68c0\u7d22\u589e\u5f3a\u4ee3\u7801\u8865\u5168\u7684\u74f6\u9888\uff0c\u5e76\u63d0\u51faMAGIC\u5206\u9636\u6bb5\u4f18\u5316\u7b56\u7565\uff0c\u6709\u6548\u63d0\u5347\u4ee3\u7801\u8865\u5168\u8d28\u91cf\u548c\u6548\u7387\uff0c\u5bf9\u76f8\u5173\u4efb\u52a1\u7684\u68c0\u7d22\u4e0e\u751f\u6210\u534f\u540c\u673a\u5236\u6709\u521b\u65b0\u6027\u542f\u793a\u3002", "method": "\u9996\u5148\u5bf9\u73b0\u6709\u68c0\u7d22\u589e\u5f3a\u65b9\u6cd5\u8fdb\u884c\u5b9a\u6027\u548c\u5b9a\u91cf\u7ecf\u9a8c\u7814\u7a76\uff0c\u8bc6\u522b\u5f71\u54cd\u4ee3\u7801\u8865\u5168\u6548\u679c\u7684\u5173\u952e\u56e0\u7d20\uff0c\u5e76\u57fa\u4e8e\u7ecf\u9a8c\u5206\u6790\uff0c\u63d0\u51fa\u4e86MAGIC\u65b9\u6cd5\u2014\u2014\u4e00\u79cd\u5206\u9636\u6bb5\u4f18\u5316\u68c0\u7d22\u7b56\u7565\u7684\u65b0\u578b\u68c0\u7d22\u589e\u5f3a\u4ee3\u7801\u8865\u5168\u6280\u672f\uff0c\u5305\u62ec\u4ee3\u7801\u5207\u5206\u3001\u4e8c\u6b21\u68c0\u7d22\u7cbe\u6392\u548c\u6a21\u677f\u63d0\u793a\u751f\u6210\u7b49\u6539\u8fdb\u63aa\u65bd\u3002", "objective": "\u7cfb\u7edf\u5206\u6790\u548c\u6539\u8fdb\u4ee3\u7801\u8865\u5168\u4efb\u52a1\u4e2d\u68c0\u7d22\u589e\u5f3a\u7b56\u7565\uff0c\u63d0\u5347\u68c0\u7d22\u4ee3\u7801\u7247\u6bb5\u5bf9\u751f\u6210\u6a21\u578b\u7684\u6b63\u9762\u4f5c\u7528\uff0c\u5e76\u51cf\u5c11\u65e0\u5173\u4ee3\u7801\u7684\u5e72\u6270\uff0c\u8fdb\u800c\u63d0\u5347\u4ee3\u7801\u8865\u5168\u7684\u51c6\u786e\u6027\u548c\u6548\u7387\u3002", "results": "\u5728Java\u4ee3\u7801\u6570\u636e\u96c6\u5b9e\u8bc1\u4e2d\uff0cMAGIC\u65b9\u6cd5\u76f8\u6bd4\u5df2\u6709\u68c0\u7d22\u589e\u5f3a\u8865\u5168\u65b9\u6cd5\uff0c\u7f16\u8f91\u76f8\u4f3c\u5ea6\u548c\u5b8c\u5168\u5339\u914d\u6307\u6807\u5206\u522b\u63d0\u53476.76%\u548c7.81%\uff1b\u76f8\u8f83\u4e8e6B\u53c2\u6570\u91cf\u7684\u4ee3\u7801\u5927\u6a21\u578b\uff0c\u5728\u5927\u5e45\u964d\u4f4e\u5185\u5b58\u6d88\u8017\u548c\u63a8\u7406\u65f6\u95f4\u7684\u524d\u63d0\u4e0b\uff0c\u7f16\u8f91\u76f8\u4f3c\u5ea6\u548c\u5b8c\u5168\u5339\u914d\u6307\u6807\u4e5f\u6709\u663e\u8457\u63d0\u5347\u3002"}


author: 高辉;陈历泉;鲁工圆
keywords: 检索增强生成;本地知识库;决策;大语言模型;高铁应急调度处置方案
source: 铁道运输与经济
site: 维普
title: 高铁应急调度处置方案的大语言模型检索增强生成方法
created_at: 2025-09-12 18:32:54.757542
original_link:
  https://www.cqvip.com/doc/journal/3507498426?sign=5cb95de58dd304e6c56812ed02046bac62ef41a5dc789f9e48d47b4cc702db48&expireTime=1789209104116&resourceId=3507498426

summary:
[cell repeats an earlier one in this file: 462 characters]

parsed_summary:
  {"background": "\u5f53\u524d\u9ad8\u901f\u94c1\u8def\u5e94\u6025\u8c03\u5ea6\u51b3\u7b56\u4e3b\u8981\u4f9d\u8d56\u4eba\u5de5\u7ecf\u9a8c\uff0c\u901a\u8fc7\u8c03\u5ea6\u5458\u4f9d\u636e\u89c4\u7ae0\u548c\u73b0\u573a\u60c5\u51b5\u4eba\u5de5\u9009\u62e9\u5e76\u8c03\u6574\u65b9\u6848\uff0c\u5b58\u5728\u51b3\u7b56\u6d41\u7a0b\u590d\u6742\u3001\u6548\u7387\u6709\u5f85\u63d0\u5347\u7684\u95ee\u9898\u3002", "contribution": "\u672c\u7814\u7a76\u57fa\u4e8e\u672c\u5730\u77e5\u8bc6\u5e93\uff0c\u9996\u6b21\u5c06\u68c0\u7d22\u589e\u5f3a\u751f\u6210\u65b9\u6cd5\u5e94\u7528\u4e8e\u9ad8\u94c1\u5e94\u6025\u8c03\u5ea6\u667a\u80fd\u51b3\u7b56\uff0c\u663e\u8457\u63d0\u5347\u4e86\u65b9\u6848\u751f\u6210\u7684\u6548\u7387\u548c\u6587\u672c\u8d28\u91cf\uff0c\u5e76\u9a8c\u8bc1\u4e86\u65b9\u6cd5\u5728\u5c0f\u53c2\u6570\u5927\u8bed\u8a00\u6a21\u578b\u4e0b\u7684\u5b9e\u7528\u6027\u3002", "method": "\u5206\u6790\u9ad8\u94c1\u5e94\u6025\u8c03\u5ea6\u51b3\u7b56\u6d41\u7a0b\uff0c\u57fa\u4e8e\u8c03\u5ea6\u5458\u5e94\u6025\u5904\u7f6e\u6307\u5bfc\u4e66\u5efa\u7acb\u672c\u5730\u77e5\u8bc6\u5e93\uff0c\u8bbe\u8ba1\u9762\u5411\u672c\u5730\u77e5\u8bc6\u5e93\u7684\u68c0\u7d22\u65b9\u6cd5\u4e0e\u63d0\u793a\u8bcd\u6a21\u677f\uff0c\u5e76\u7ed3\u5408\u5927\u8bed\u8a00\u6a21\u578b\u5b9e\u73b0\u65b9\u6848\u7684\u81ea\u52a8\u751f\u6210\u4e0e\u4fee\u6b63\u3002", "objective": "\u63d0\u51fa\u4e00\u79cd\u5229\u7528\u5927\u8bed\u8a00\u6a21\u578b\u5e76\u7ed3\u5408\u672c\u5730\u77e5\u8bc6\u5e93\u7684\u68c0\u7d22\u589e\u5f3a\u751f\u6210\u65b9\u6cd5\uff0c\u4ee5\u63d0\u5347\u9ad8\u94c1\u5e94\u6025\u8c03\u5ea6\u5904\u7f6e\u65b9\u6848\u7684\u51b3\u7b56\u6548\u7387\u548c\u8d28\u91cf\u3002", "results": "\u6240\u63d0\u65b9\u6cd5\u5728BLEU\u3001ROUGE\u7b49\u6587\u672c\u751f\u6210\u4e0e\u7ea0\u9519\u6307\u6807\u4e0a\u8868\u73b0\u51fa\u8272\uff0c\u4e3b\u6d41\u6a21\u578b\u4e0b\u7ea0\u9519\u6b63\u786e\u7387\u9ad8\u8fbe89.77%\uff1b\u5728\u53c2\u6570\u91cf\u8f83\u5c0f\u7684\u5927\u8bed\u8a00\u6a21\u578b\u6761\u4ef6\u4e0b\u4e5f\u80fd\u4fdd\u6301\u8f83\u9ad8\u6027\u80fd\uff0c\u663e\u793a\u51fa\u65b9\u6cd5\u7684\u6709\u6548\u6027\u4e0e\u901a\u7528\u6027\u3002"}


author: 张錋;张道娟;陈凯;赵宇飞;张英杰
date: 2025-09-11 11:01
keywords: 对抗性防御;;检索增强分类;;自然语言处理;;模型鲁棒性;;KNN检索;;表征学习;
source: 计算机科学
site: 知网
title: 基于检索增强分类与解耦表示的NLP对抗鲁棒性提升方法
created_at: 2025-09-12 18:34:20.158639
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4keW74pC7kbVR3wEYQUUhQOkcySm7hIs9ltF7j4bedWi8ca4NJq4_cljuZMNe2qmhGgXXH_i7jey1yvk0_5GhjPEvhzkOpEA5QnBJ56v0dyzrDvakVl5G6JnBdysudT6q37gmCS1OlArg5Dlhd2EoAy56RTdBQd0vR7peK5fZ3nUTg==&uniplatform=NZKPT&language=CHS

summary:
[cell repeats an earlier one in this file: 358 characters]

parsed_summary:
  {"background": "\u5c3d\u7ba1NLP\u6a21\u578b\u5728\u6587\u672c\u5206\u7c7b\u4efb\u52a1\u4e2d\u8868\u73b0\u51fa\u8272\uff0c\u4f46\u5728\u5bf9\u6297\u6027\u653b\u51fb\u9762\u524d\u4f9d\u7136\u5c55\u73b0\u51fa\u663e\u8457\u8106\u5f31\u6027\uff0c\u4e9f\u9700\u63d0\u5347\u6a21\u578b\u7684\u9c81\u68d2\u6027\u4ee5\u5e94\u5bf9\u5b89\u5168\u5a01\u80c1\u3002", "contribution": "\u63d0\u51fa\u4e86\u68c0\u7d22\u589e\u5f3a\u4e0e\u8868\u5f81\u89e3\u8026\u8054\u5408\u63d0\u5347\u6a21\u578b\u9c81\u68d2\u6027\u7684\u7b56\u7565\uff0c\u4e3aNLP\u7cfb\u7edf\u5bf9\u6297\u6027\u9632\u5fa1\u63d0\u4f9b\u4e86\u65b0\u601d\u8def\u548c\u5b9e\u8bc1\u6548\u679c\uff0c\u5177\u6709\u5b9e\u9645\u5e94\u7528\u4e0e\u7406\u8bba\u4ef7\u503c\u3002", "method": "\u672c\u6587\u91c7\u7528\u68c0\u7d22\u589e\u5f3a\u5206\u7c7b\u65b9\u6cd5\uff0c\u7ed3\u5408KNN\u76f8\u4f3c\u6837\u672c\u6807\u7b7e\u5206\u5e03\u4e0e\u6a21\u578b\u81ea\u8eab\u9884\u6d4b\uff0c\u5e76\u5c06\u5206\u7c7b\u4e0e\u68c0\u7d22\u7684\u7279\u5f81\u8868\u793a\u7a7a\u95f4\u8fdb\u884c\u89e3\u8026\u8bbe\u8ba1\uff0c\u4ece\u800c\u63d0\u5347\u6027\u80fd\u4e0e\u8bad\u7ec3\u7a33\u5b9a\u6027\u3002", "objective": "\u63d0\u51fa\u80fd\u591f\u6709\u6548\u63d0\u5347NLP\u6a21\u578b\u5bf9\u6297\u9c81\u68d2\u6027\u7684\u521b\u65b0\u65b9\u6cd5\uff0c\u51cf\u8f7b\u5bf9\u6297\u653b\u51fb\u5e26\u6765\u6027\u80fd\u9aa4\u964d\u7684\u95ee\u9898\u3002", "results": "\u5728\u591a\u79cd\u57fa\u51c6\u6570\u636e\u96c6\u548c\u4e0d\u540c\u5bf9\u6297\u573a\u666f\u4e0b\uff0c\u8be5\u65b9\u6cd5\u5b9e\u73b0\u4e86\u5bf9\u6297\u51c6\u786e\u7387\u4e0b\u964d\u5e45\u5ea6\u51cf\u5c1130-40\u4e2a\u767e\u5206\u70b9\uff0c\u5e76\u5728\u5f3a\u653b\u51fb\u4e0b\u4f9d\u7136\u4fdd\u6301\u7a33\u5b9a\u8868\u73b0\uff0c\u9a8c\u8bc1\u4e86\u65b9\u6cd5\u7684\u6709\u6548\u6027\u3002"}


author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-12 18:34:20.159236
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCDY5a3ppdWNh

summary:
[cell repeats an earlier one in this file: 822 characters]

parsed_summary:
  {"background": "\u5728\u8f6f\u4ef6\u5f00\u53d1\u8fc7\u7a0b\u4e2d\uff0c\u5f00\u53d1\u8005\u5e38\u5e38\u53c2\u8003\u5df2\u6709\u7684\u7c7b\u4f3c\u4ee3\u7801\u7247\u6bb5\uff0c\u800c\u5f53\u524d\u7684\u4ee3\u7801\u8865\u5168\u6a21\u578b\u4e5f\u5c1d\u8bd5\u901a\u8fc7\u68c0\u7d22\u5e76\u5229\u7528\u5916\u90e8\u4ee3\u7801\u6765\u63d0\u5347\u751f\u6210\u6548\u679c\uff0c\u4f46\u73b0\u6709\u7684\u7b80\u5355\u62fc\u63a5\u68c0\u7d22\u548c\u8f93\u5165\u4ee3\u7801\u7684\u65b9\u6cd5\u5b58\u5728\u5f15\u5165\u566a\u58f0\u548c\u4f9d\u8d56\u68c0\u7d22\u51c6\u786e\u6027\u7684\u95ee\u9898\uff0c\u53ef\u80fd\u5f71\u54cd\u4ee3\u7801\u8865\u5168\u7684\u51c6\u786e\u6027\u548c\u5b9e\u7528\u6027\u3002", "contribution": "\u8bba\u6587\u7cfb\u7edf\u5206\u6790\u4e86\u68c0\u7d22\u589e\u5f3a\u4ee3\u7801\u8865\u5168\u7684\u5173\u952e\u5f71\u54cd\u56e0\u7d20\uff0c\u63d0\u51fa\u4e86\u521b\u65b0\u6027\u7684\u591a\u9636\u6bb5\u4f18\u5316\u68c0\u7d22\u7b56\u7565\uff0c\u6709\u6548\u63d0\u5347\u4e86\u4ee3\u7801\u8865\u5168\u7684\u51c6\u786e\u6027\u548c\u6548\u7387\uff0c\u4e3a\u4ee3\u7801\u751f\u6210\u6a21\u578b\u7684\u5b9e\u9645\u5e94\u7528\u5e26\u6765\u65b0\u7684\u601d\u8def\u548c\u65b9\u6cd5\u3002", "method": "\u9996\u5148\u901a\u8fc7\u5b9a\u6027\u548c\u5b9a\u91cf\u5b9e\u9a8c\u5206\u6790\u68c0\u7d22\u589e\u5f3a\u5404\u9636\u6bb5\u5bf9\u8865\u5168\u6548\u679c\u7684\u5f71\u54cd\uff0c\u8bc6\u522b\u5173\u952e\u5f71\u54cd\u56e0\u7d20\uff1b\u5728\u6b64\u57fa\u7840\u4e0a\u63d0\u51faMAGIC\u65b9\u6cd5\uff0c\u91c7\u7528\u591a\u9636\u6bb5\u4f18\u5316\u7684\u68c0\u7d22\u7b56\u7565\uff0c\u5305\u62ec\u4ee3\u7801\u5207\u5206\u3001\u4e8c\u6b21\u68c0\u7d22\u7cbe\u6392\u548c\u6a21\u677f\u63d0\u793a\u751f\u6210\u7b49\u7b56\u7565\u3002", "objective": "\u91cd\u65b0\u5206\u6790\u548c\u6539\u8fdb\u4ee3\u7801\u8865\u5168\u4efb\u52a1\u4e2d\u7684\u68c0\u7d22\u589e\u5f3a\u7b56\u7565\uff0c\u964d\u4f4e\u68c0\u7d22\u8bef\u5dee\u5bf9\u751f\u6210\u6a21\u578b\u7684\u8d1f\u9762\u5f71\u54cd\uff0c\u5e76\u63d0\u5347\u4ee3\u7801\u8865\u5168\u7ed3\u679c\u7684\u8d28\u91cf\u548c\u6548\u7387\u3002", "results": "MAGIC\u65b9\u6cd5\u5728Java\u6570\u636e\u96c6\u4e0a\u7684\u5b9e\u9a8c\u663e\u793a\uff0c\u76f8\u6bd4\u73b0\u6709\u68c0\u7d22\u589e\u5f3a\u8865\u5168\u65b9\u6cd5\uff0c\u7f16\u8f91\u76f8\u4f3c\u5ea6\u548c\u5b8c\u5168\u5339\u914d\u6307\u6807\u5206\u522b\u63d0\u53476.76%\u548c7.81%\uff1b\u4e0e\u53c2\u6570\u91cf\u4e3a6B\u7684\u4ee3\u7801\u5927\u6a21\u578b\u76f8\u6bd4\uff0c\u5728\u663e\u5b58\u548c\u63a8\u7406\u65f6\u95f4\u663e\u8457\u8282\u7701\u7684\u60c5\u51b5\u4e0b\uff0c\u8865\u5168\u6548\u679c\u8fdb\u4e00\u6b65\u63d0\u5347\u3002"}


author: 高辉;陈历泉;鲁工圆
keywords: 检索增强生成;本地知识库;决策;大语言模型;高铁应急调度处置方案
source: 铁道运输与经济
site: 维普
title: 高铁应急调度处置方案的大语言模型检索增强生成方法
created_at: 2025-09-12 18:34:20.159694
original_link:
  https://www.cqvip.com/doc/journal/3507498426?sign=5e1addf288a6143937196b1ad6fe843d9f1ab90652e50703331b6e242087ad8f&expireTime=1789209183203&resourceId=3507498426

summary:
[cell repeats an earlier one in this file: 462 characters]

parsed_summary:
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author: 张錋;张道娟;陈凯;赵宇飞;张英杰
date: 2025-09-11 11:01
keywords: 对抗性防御;;检索增强分类;;自然语言处理;;模型鲁棒性;;KNN检索;;表征学习;
source: 计算机科学
site: 知网
title: 基于检索增强分类与解耦表示的NLP对抗鲁棒性提升方法
created_at: 2025-09-12 18:35:45.357305
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4keHCT7fs1il_-vUXGSIs3F2zm-TJtU2PXGQ-ylYvWi7irxQksXVtNLCxBgj9NdNU2JsyTQbJAiQUKZeT8deWmzl_CzK9mFFiY2_wW716QS-8cXS2cOj43nXD2wv6vReP2olCeHcSaq5RX5zXmItq57xWxEq1IwI_RrRDVMJQIOS5g==&uniplatform=NZKPT&language=CHS

summary:
[cell repeats an earlier one in this file: 358 characters]

parsed_summary:
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author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-12 18:35:45.360027
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCGZqbzJvb2Js

summary:
[cell repeats an earlier one in this file: 822 characters]

parsed_summary:
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author: 金哲;邹健;李逍;吕嘉欣;胡中旭
date: 2025-08-28
keywords: 大语言模型;;检索增强生成;;“幻觉”问题;;医学信息检索;
source: 药物流行病学杂志
site: 知网
title: 检索增强生成技术在医学人工智能中的应用与前沿探索
created_at: 2025-09-12 18:37:07.278448
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4keGA1KQC-n4oGH36defp__eO70r443GASe3GGBIfaCdb0OeNUuZ_ux7-NnthIk4RhX6tZiSap2nPsY-FAK303-UwNsPveRA2Pk34WbMLdxJ7dR-kXcJcZmr2u5dlubuM20m7BMDbYu0TVcXJJZQB-6PeIK3YrzkYvshcttcg144UQ==&uniplatform=NZKPT&language=CHS

summary:
  随着大语言模型（LLM）的蓬勃兴起，深度学习的自然语言生成能力在医学领域展现出了显著价值。然而模型参数的“封闭性”易导致其产生“幻觉”，难以对最新知识作出准确回答，且推理过程缺乏透明度与溯源。检索增强生成（RAG）技术通过在生成阶段主动连接外部文献数据库、知识图谱等信息源，大幅降低了LLM对过时训练数据的依赖，并在回答中引入可验证的证据和实时更新的知识。在医学领域，RAG技术有效解决了文献检索与临床决策支持中的高准确度与可追溯性需求，广泛应用于新药研发、药物警戒、罕见病诊疗等方面。结合强化学习、多模态处理与合规隐私保护等新兴技术，RAG技术正朝着更加开放、高度定制化的方向演进，为医学信息检索与辅助决策提供了全新的智能化解决方案。

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author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-12 18:37:07.281206
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCDR3dHAxdGYx

summary:
[cell repeats an earlier one in this file: 822 characters]

parsed_summary:
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author: 高辉;陈历泉;鲁工圆
keywords: 检索增强生成;本地知识库;决策;大语言模型;高铁应急调度处置方案
source: 铁道运输与经济
site: 维普
title: 高铁应急调度处置方案的大语言模型检索增强生成方法
created_at: 2025-09-12 18:37:07.283350
original_link:
  https://www.cqvip.com/doc/journal/3507498426?sign=91d4bb914965c9653f2cd8c7f11283c6b9a82431a6764fca59dbb3698f280553&expireTime=1789209353885&resourceId=3507498426

summary:
[cell repeats an earlier one in this file: 462 characters]

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author: 张錋;张道娟;陈凯;赵宇飞;张英杰
date: 2025-09-11 11:01
keywords: 对抗性防御;;检索增强分类;;自然语言处理;;模型鲁棒性;;KNN检索;;表征学习;
source: 计算机科学
site: 知网
title: 基于检索增强分类与解耦表示的NLP对抗鲁棒性提升方法
created_at: 2025-09-12 18:38:11.380692
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kfVBXsnoe0w0lvA2b332-Hs1xvyTtf6W3ciLbrDGZZxycy0qkZUKGWH__j_SxmB-4pEDm7b33WNSfPnWWpLP59Wjh2kd1G2_iMVz4o1Tw1aT3SDLN2DyhRKxdDic3oTPF1rF28Qm9JhzrOZGGhTo6Ge-K176qBc7r9CbXKp4NAz3A==&uniplatform=NZKPT&language=CHS

summary:
[cell repeats an earlier one in this file: 358 characters]

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author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-12 18:38:11.383404
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCDJqYmVieWpl

summary:
[cell repeats an earlier one in this file: 822 characters]

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author: 金哲;邹健;李逍;吕嘉欣;胡中旭
date: 2025-08-28
keywords: 大语言模型;;检索增强生成;;“幻觉”问题;;医学信息检索;
source: 药物流行病学杂志
site: 知网
title: 检索增强生成技术在医学人工智能中的应用与前沿探索
created_at: 2025-09-12 18:39:25.417257
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4keurKfkYh5UGZMwg1GFfNsimH9K3LSBJGvSjJLrgyIlmLeK2DBwCe9n9fTPHj81VesBmihYM0NheYsFQsHooc6TSIu2-YUPWepuQmZ17gchTqJN-_jfeWO7p0GsRU2VoUnolSVxPZwEmDBThsfqfmO6NwQ84m3u1x5M3uZi2-NQEQ==&uniplatform=NZKPT&language=CHS

summary:
  随着大语言模型（LLM）的蓬勃兴起，深度学习的自然语言生成能力在医学领域展现出了显著价值。然而模型参数的“封闭性”易导致其产生“幻觉”，难以对最新知识作出准确回答，且推理过程缺乏透明度与溯源。检索增强生成（RAG）技术通过在生成阶段主动连接外部文献数据库、知识图谱等信息源，大幅降低了LLM对过时训练数据的依赖，并在回答中引入可验证的证据和实时更新的知识。在医学领域，RAG技术有效解决了文献检索与临床决策支持中的高准确度与可追溯性需求，广泛应用于新药研发、药物警戒、罕见病诊疗等方面。结合强化学习、多模态处理与合规隐私保护等新兴技术，RAG技术正朝着更加开放、高度定制化的方向演进，为医学信息检索与辅助决策提供了全新的智能化解决方案。

parsed_summary:
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author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-12 18:39:25.420009
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCGx3dHZkejU2

summary:
[cell repeats an earlier one in this file: 822 characters]

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author: 高辉;陈历泉;鲁工圆
keywords: 检索增强生成;本地知识库;决策;大语言模型;高铁应急调度处置方案
source: 铁道运输与经济
site: 维普
title: 高铁应急调度处置方案的大语言模型检索增强生成方法
created_at: 2025-09-12 18:39:25.422517
original_link:
  https://www.cqvip.com/doc/journal/3507498426?sign=b54ebfe1cc948eecd92c7987635e04934f68e92c3e533d89d8c14b3c6671cdea&expireTime=1789209499526&resourceId=3507498426

summary:
[cell repeats an earlier one in this file: 462 characters]

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author: 张錋;张道娟;陈凯;赵宇飞;张英杰
date: 2025-09-11 11:01
keywords: 对抗性防御;;检索增强分类;;自然语言处理;;模型鲁棒性;;KNN检索;;表征学习;
source: 计算机科学
site: 知网
title: 基于检索增强分类与解耦表示的NLP对抗鲁棒性提升方法
created_at: 2025-09-12 18:40:32.591876
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=d7HKHDfP4kevkYTQLnrFjRNTFEE6eLDaNFVdDZYP3lbTi6l5iZEDwYKgMIV-uwxBeLS6ySFApsneO2Bbm9nD6stS8w3pxju3KtrjBFmUEPSobwvrfRZt4fP07oP4VcUKZjLN2TmAyYak1Pe3CeQKV3Mx57rVBmJHM4sF8f6goPNcfHJWjMEzmw==&uniplatform=NZKPT&language=CHS

summary:
[cell repeats an earlier one in this file: 358 characters]

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author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-12 18:40:32.594492
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCDR5cW53N3A1

summary:
[cell repeats an earlier one in this file: 822 characters]

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author: 张錋;张道娟;陈凯;赵宇飞;张英杰
date: 2025-09-11 11:01
keywords: 对抗性防御;;检索增强分类;;自然语言处理;;模型鲁棒性;;KNN检索;;表征学习;
source: 计算机科学
site: 知网
title: 基于检索增强分类与解耦表示的NLP对抗鲁棒性提升方法
created_at: 2025-09-15 10:47:04.319100
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYHZhUKcOg3aihwgPqQlLZkOBKX3jdKTn_ypHuPf5CuLZuXh02vEbvT-PUbqbsH1d1AeutSXbTjdeupvmP0KRuMv2mF1wBELqzvXbMsofZMNXPtDHbk-vSpmb66pvCHZ7_BrpyW4UiNZwFszGLfulhbUSadn-BSz2XJLnB1sY_bhIw==&uniplatform=NZKPT&language=CHS

summary:
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author: 邹佰翰;汪莹;彭鑫
date: 2025年6期
keywords: 检索增强;大语言模型;代码补全;提示学习;多阶段优化
quote: 1
source: 《软件学报》
site: 万方
title: 重新审视代码补全中的检索增强策略
created_at: 2025-09-15 10:47:04.321742
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDYwMTUaCHF5Y2I2d3hy

summary:
[cell repeats an earlier one in this file: 822 characters]

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author: Zhuowei Zhao;Zhuo Zhang;Hanzhi Wang;Junhao Gan;Zhifeng Bao;Jianzhong Qi
date: 12 September, 2025
original_link: https://arxiv.org/abs/2509.10036
pdf_url: https://arxiv.org/pdf/2509.10036
site: arxiv
created_at: 2025-09-15 10:47:04.322571
summary:
  Abstract:We revisit Approximate Graph Propagation (AGP), a unified framework which captures various graph propagation tasks, such as PageRank, feature propagation in Graph Neural Networks (GNNs), and graph-based Retrieval-Augmented Generation (RAG). Our work focuses on the settings of dynamic graphs and dynamic parameterized queries, where the underlying graphs evolve over time (updated by edge insertions or deletions) and the input query parameters are specified on the fly to fit application needs. Our first contribution is an interesting observation that the SOTA solution, AGP-Static, can be adapted to support dynamic parameterized queries; however several challenges remain unresolved. Firstly, the query time complexity of AGP-Static is based on an assumption of using an optimal algorithm for subset sampling in its query algorithm. Unfortunately, back to that time, such an algorithm did not exist; without such an optimal algorithm, an extra O(\log^2 n) factor is required in the query complexity, where n is the number of vertices in the graphs. Secondly, AGP-Static performs poorly on dynamic graphs, taking O(n\log n) time to process each update. To address these challenges, we propose a new algorithm, AGP-Static++, which is simpler yet reduces roughly a factor of O(\log^2 n) in the query complexity while preserving the approximation guarantees of AGP-Static. However, AGP-Static++ still requires O(n) time to process each update. To better support dynamic graphs, we further propose AGP-Dynamic, which achieves O(1) amortized time per update, significantly improving the aforementioned O(n) per-update bound, while still preserving the query complexity and approximation guarantees. Last, our comprehensive experiments validate the theoretical improvements: compared to the baselines, our algorithm achieves speedups of up to 177\times on update time and 10\times on query efficiency.

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title:
  Approximate Graph Propagation Revisited: Dynamic Parameterized Queries, Tighter Bounds and Dynamic Updates


author: 肖克江;陈亮;方铄;庞世燕;邱杰凡
date: 2025-09-10 16:14
keywords: 在线课程;;推荐系统;;知识图谱;;图注意力网络;;特征交叉;
source: 数据分析与知识发现
site: 知网
title: 融合课程知识图谱与图注意力网络的推荐模型研究
created_at: 2025-09-15 11:08:15.264650
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYFJ78iAelUFZGO_XTpWLxGMgiRNcS5uclnnNa1ntiByG6PhKyiWje1Zp5sNgw8LmxOEUuEihRjEnV2YeWISuKvqokz3PmdmUHyRn_Bmfg5_EUzdLrAG0tzqaeYK-NEHbaPBvBs2iKeT_NXPareQdBic3JXQkGQ4RdOuumqypltiNw==&uniplatform=NZKPT&language=CHS

summary:
  [目的]针对在线课程推荐存在数据稀疏、冷启动和特征利用不充分的问题，本文提出了一种融合课程知识图谱与图注意力网络的推荐模型（CKGAT）。[方法]CKGAT的学习者模块通过特征交叉层和全连接层分别提升学习者特征的记忆和泛化能力，课程模块基于图注意力网络挖掘课程实体间的高阶语义特征。本文对两个模块的输出向量进行点积计算后，得到推荐结果。[结果]在基于MoocCubeX数据集的对比实验中，CKGAT在ACC、F1和AUC指标上相较于最好的基线模型分别提升了1.28%、1.62%和1.00%。[局限]本文的课程知识图谱略显单薄，模型的计算复杂度可进一步优化。[结论]本文提出的CKGAT取得了较好的推荐结果，有助于提升在线课程推荐效果。

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author: 敖若瑶
date: 2025-09-09
keywords: 知识图谱;;文化遗产;;数字人文;;大模型;
source: 科技与创新
site: 知网
title: 文化遗产领域知识图谱发展趋势与前沿进展研究
created_at: 2025-09-15 11:08:15.265347
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYGFHC6qO8pjUxGHLQ4MVixM6fAtZU63gmVsLd8O10HzXY8yUMbmbhci66p_NLfNAi8DsaYrVxrN05SqueJrjsTcr5cm5z6Wq760xqb3pZa6OpCcqx3QaQc0k5j9DcHcT-INgyZhc0X-AZO1d6ESnRvmX7ML-OCeJ-rhrALHVaY9sQ==&uniplatform=NZKPT&language=CHS

summary:
  知识图谱作为学界较为成熟的一项技术，为分散且多维度的文化遗产资源提供了结构化与语义化整合的解决方案。运用文献计量法和文献分析法，借助CiteSpace软件对从CNKI期刊库中获取的共计92篇相关文献进行科学知识图谱可视化分析，旨在揭示文化遗产领域知识图谱研究的演进脉络、热点主题以及前沿趋势。研究总结归纳出文化领域知识图谱研究的演进可划分为3个阶段，即萌芽期（2015—2019年）、发展期（2020—2023年）、探索期（2024—2025年），发现大模型与智能体技术显著推动了文化遗产知识图谱在知识生成、多模态交互以及动态服务方面的革新。展望未来，可以重点关注多模态知识图谱的深度整合与动态表达，以及智能体驱动的主动化知识服务系统等方向，以深化文化遗产的智慧化保护与传播。

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author: 王菁;刘丹
date: 2025-09-02
keywords: 思政课;;知识图谱;;精准教学;
source: 思想理论教育
site: 知网
title: 基于知识图谱的思政课精准教学探析
created_at: 2025-09-15 11:08:15.265834
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYGFHC6qO8pjUxGHLQ4MVixM6fAtZU63gmUKMKcQYsLs2QQwDwtamZr4G4mpHqABy4-teXM7fIFRyLY291i7l-bl9EB3wtjdkOmPVOJSRgA3d5s2eLT_2U3C0ZaHnAeqiY22e5-xS5ZJD_6R_vckyOCs1BNfvH3irPbjy0iclumVow==&uniplatform=NZKPT&language=CHS

summary:
  运用知识图谱技术构建思政课知识图谱，是推动思政课精准教学的必要举措。知识图谱赋能高校思政课精准教学就在于其在推动教学内容的贯通性与针对性、把握教育对象的群体性与个体性、促进教学全过程和全要素评价等方面具有重要价值。基于此，应构建框架与流程，打造全面、系统且可交互的思政课知识图谱，并从精准描摹画像、高效利用资源、评估实时学情等方面积极探索实施路径，以此实现个性化学习路径推荐、针对性教学内容供给、教与学成效即时反馈，从而提高思政课教学的针对性和实效性。

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author: 张宝一;唐嘉成;张彤蕴;王宾海;史与正
date: 2025-09-01 10:48
keywords: 地质找矿;;知识图谱;;大语言模型;;检索增强生成;;地质本体;;思维链;
source: 地球科学
site: 知网
title: 大语言模型赋能的地质找矿知识图谱与问答模型构建
created_at: 2025-09-15 11:08:15.266306
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYGjjLOAhvBs-wpo2ij-nR92DQnGABR2PIdD6aRAlqR-2ilzFqq0VrBpggx8iGEdao5RMH1XgEAtO_5jmUXgVem--SA2MF5QwzwKhPdrydkIb2KHQ1KXg5bHGcaQz0Rqco9Uo4rgWkk1fGq4lcX8Nq7gyXUSdVMrV_vJXU_gOTomnw==&uniplatform=NZKPT&language=CHS

summary:
  当前地质找矿领域的大语言模型应用面临着专业知识不足、数据隐私安全和模型幻觉等问题，同时大语言模型在地质找矿领域应用中仍缺乏高效快捷的知识推荐手段。本研究提出了知识图谱与检索增强生成相结合的KG-RAG (Knowledge graph Retrieval-Augmented Generation) 框架，以大语言模型为工具，在地质本体约束下实现了地质找矿知识图谱的自动化抽取和结构化表达，同时利用知识图谱的多跳检索算法实现检索内容的深度与广度优化，实现了地质找矿智能知识问答模型。实验结果表明：KG-RAG在准确率、召回率和可信度(F1-score)上分别取得的0.807、0.833和0.819，在知识图谱构建任务相比大语言基模型GLM4-9B的直接知识抽取，分别取得了约50%、8%和29%的提升；在问答任务中，KG-RAG召回率和准确率上分别取得了0.917和0.88，相比文档向量检索增强生成方法分别取得了约24%和22%的提升。KG-RAG在知识图谱构建与智能问答两方面均表现出了较好的性能，能够有效从地质资料中进行地质找矿知识收集与表达，支持地质工作者的地质调查与找矿预测工作，本研究为...

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author: 敖若瑶
date: 2025-08-25
keywords: 知识图谱;;人工智能;;大模型;;向量数据库;
source: 现代信息科技
site: 知网
title: 知识图谱演进与新兴技术融合趋势研究
created_at: 2025-09-15 11:08:15.266793
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYGjjLOAhvBs-wpo2ij-nR92fXEkfCRaeLvil_TIR5_ecRe1l_wq1P37sInVo_B8Snsmy9LHe3QVER6BgULc6u0bSn4uH9uD_oOAHpgxMgC37fUPENyF6CiK-qG9uE-UKTZ429POvKbmkHp1SrgpvKaczYfksVvbuKAQNoz6RBs93Q==&uniplatform=NZKPT&language=CHS

summary:
  文章系统梳理了知识图谱的演变进展及其与大模型、向量数据库、智能体新兴技术的融合研究进展，旨在为未来知识图谱的发展提供理论框架与实践指引。首先通过从多维视角讨论知识图谱的演变，包括应用范围、知识变化特性和数据表现形式。随后探讨了其与大模型、向量数据库和智能体的前沿交互进展。知识图谱的发展展现了从一般到垂直、从静态到动态、从单一到多元的转变。未来的知识图谱研究应更加注重动态知识图谱的构建、多模态大模型的融合以及与新兴技术的交互实现，以适应人工智能和大数据时代的需求。

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author: 梁娜;张倩瑜;张晓庆;周超;蔡婷婷
date: 2025-08-25
keywords: 护理本科生;;知识图谱;;BOPPPS模式;;围手术期护理;;外科护理学;;课程思政;;自主学习能力;;护理教育;
source: 护理学杂志
site: 知网
title: 基于知识图谱的BOPPPS模式在围手术期护理教学中的应用
created_at: 2025-09-15 11:08:15.267269
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYGjjLOAhvBs-wpo2ij-nR92fXEkfCRaeLuAWp4J_ZHte5WFtaEGgjxX5KpbcalUIc18sFwT0tiGlYhr7-YykQDAd6MnxZIxX8Jj853-xXhvaKrJpmKPy9daNKVg0KS73_1c3vCg1tM92UIYfVaPnRSkpl1T2RsfacwNN6K05UTnxg==&uniplatform=NZKPT&language=CHS

summary:
  目的 构建并评估基于知识图谱的BOPPPS模式在围手术期护理教学的应用效果。方法 便利抽取2022级4个护理本科班级，按班级随机分为对照组和试验组各79人。对照组实施常规围手术期护理教学，试验组依托超星泛雅平台的知识图谱技术，构建围手术期护理知识图谱体系，包括知识图谱、问题图谱和课程思政图谱，实施基于知识图谱的BOPPPS教学。课程结束后比较两组考核成绩与自主学习能力，并结合质性访谈分析知识图谱的使用体验与效果。结果 对照组78人、试验组79人完成研究。课程结束后，试验组理论成绩、总成绩和自主学习能力评分显著高于对照组(均P<0.05),两组操作成绩差异无统计学意义(P>0.05)。访谈共提炼5个主题，知识图谱教学能提升学习获得感与使用意愿，促进知识理解与高效记忆等。结论 基于知识图谱的BOPPPS模式在围手术期护理教学中的应用，可有效提升护理本科生学习成绩与自主学习能力，强化知识整合与职业认同。

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author: 段一凡;刘然;刘小杰;张玉洁;靳亚涛
date: 2025-08-21 19:18
keywords: 强化冶炼;;高炉专家系统;;知识推理;;知识图谱;;语义网络;
source: 中国冶金
site: 知网
title: 知识图谱在高炉专家系统中的应用前景
created_at: 2025-09-15 11:08:15.267743
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYEK0DU_hlFBwUOM1QGM4OsAjWOKBjroSiTlwid-o1uIONbVMQITvuSXSuhp0QpanOXfQjXjKg7r-8oNhB46Bu5oggfHkKsARYHWll87RZek24uPsU0GQjU88RsDaZm4k4KVrIic7IccjyP0UO5sAPea9UGQ1ploZj6Pwp5fDegqfA==&uniplatform=NZKPT&language=CHS

summary:
  受限于知识推理模式的局限性，中国传统高炉专家系统在日益复杂的工况下逐渐表现出劣势，难以实现跨高炉场景的大规模推广。知识图谱是一种基于图结构数据的新型信息管理检索技术。首先，梳理了中国传统高炉专家系统的搭建机制，包括基于规则与逻辑、基于典型案例以及基于冶金数学模型3种知识推理模式，并深入分析了当前面临的痛点问题。其次，探索了高炉大数据背景下的知识图谱构建方法，并以先前工作为基础构建了以铁水钒含量为目标节点的知识图谱网络示例，绘制了相关的参数调控富集网络，验证了知识图谱在解耦多参数关联作用方面的优势。最后，总结了知识图谱技术在高炉专家系统中的应用方向，包括但不限于多模态数据的检索与管理、多参数关联作用的解耦、工艺的动态调控与优化、炉况的智能诊断、智能化决策的动态生成与推荐5个方面。知识图谱能够有效解决传统高炉专家系统规则复杂度高、单向检索、自适应能力不足等问题，促进传统基于规则的参数调控方法向全方位数据驱动的智能决策转变。知识图谱技术的高效利用是未来高炉专家系统转型与升级的重要方向。

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author: 刘启恒;李雪莲;孙孟娜
date: 2025-08-20
keywords: 知识图谱;;CiteSpace与SciExplorer-LDGAS;;文献计量分析;;网络安全;;网络空间命运共同体;;人工智能技术;
source: 南京师大学报(自然科学版)
site: 知网
title: 跨平台工具链探索网络安全知识图谱研究进展与趋势
created_at: 2025-09-15 11:08:15.268200
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYEK0DU_hlFBwUOM1QGM4OsAB5qpmfsmfowsM8x7SJPn9EMhdREVYg-oIdYVzbn3TT3E0wUrx6dOb6CRqAL8ilH-3jGb83-QNbnAlHdcerxeG-YHnhZj8pfy-y1qMX0lt76w4DG8UqUQT9b05AToYNJnWNVLciqmC2lX6IlfBpa67w==&uniplatform=NZKPT&language=CHS

summary:
  在数字化时代，网络安全已成为全球性挑战.网络攻击手段的日益复杂和多变对网络安全领域的研究提出了更高的要求.本研究基于文献计量方法，融合CiteSpace与SciExplorer-LDGAS工具链，对2011—2024年间的343篇中英文文献(含CNKI中文核心文献84篇、Web of Science核心英文文献259篇)进行系统性分析，探究网络安全知识图谱领域的研究趋势、合作网络及热点演变.研究结果表明：(1)该领域发文量自2017年起显著增长，2023—2024年达到峰值，反映计算机技术的发展与学术关注度的增强；(2)作者与机构合作呈现区域性聚集特征，中美两国研究贡献领先(分别占比27%和25%),欧美国家合作较多，但其余跨国合作网络稀疏；(3)关键词分析揭示国内外研究侧重差异：国内聚焦技术突破，国外则侧重应用优化；中英文文献也呈现出显著趋同性，具体聚焦于网络威胁情报、本体构建以及人工智能(AI)等核心方向；(4)研究热点从早期“态势感知”“可视分析”向“知识图谱构建”“攻击模式预测”演进，凸显人工智能技术驱动的防御体系升级需求.基于此，本文提出需加强跨国、跨机构协作，建立统一的知识...

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author: 商惠华
date: 2025-08-20
keywords: 知识图谱;;MOOC;;可视化;;计算机科学与技术(师范)专业课程;
source: 数字通信世界
site: 知网
title: 基于MOOC平台和知识图谱的专业学习规划研究
created_at: 2025-09-15 11:08:15.268641
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYGAixij6fmjESxNA6z9gC-ly-UJt-6T0qBPWegNNHSP-gU8uF4r3UfgADffozhZQTixwNvTcwJ-32aExzJBW45joEcCgKBUuJfGHiLjkHZquHGw-lLppzco7-4lBMaPkNJN0LwLIO8KG7M2yuZfMEZFgPx-t_0LV9Ls2B1XGG6E0Q==&uniplatform=NZKPT&language=CHS

summary:
  在国家倡导“数字化转型，推动教育高质量发展”的背景下，知识图谱的巨大潜力在教育领域得以彰显。本研究以计算机科学与技术(师范)专业为例，整合MOOC丰富教学资源，深入剖析专业课程架构与学习需求，构建专业知识图谱和课程知识图谱，并借助码投图谱数据库实现可视化呈现。通过该图谱，学习者能从宏观把握专业课程框架，从微观获取具体课程的MOOC学习资源。为检验其应用效果，对相关专业学生开展问卷调查，结果显示知识图谱在辅助学生课外自主学习、引导学习方向、提升学习效率方面成效显著。本研究为教育领域应用知识图谱优化学习规划提供了实践参考，也为后续研究奠定了基础。

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author: 周海
date: 2025-08-19 12:50
keywords: 知识图谱;;物理化学;;搭建;;面临的问题;
source: 大学化学
site: 知网
title: 物理化学I课程知识图谱设计与建设初探
created_at: 2025-09-15 11:08:15.269104
original_link:
  https://kns.cnki.net/kcms2/article/abstract?v=w3MPIJRjtYGAixij6fmjESxNA6z9gC-lCdvIt0iomu6ge178sgVR1cL94tcp5cnwBk_eC00h806ieDO6f_HpDUrcH02arVICH6G4rh8ZDgt6IYUeJUEayQyT6CZ3z5CEkpaMekhbhjt7W1RFpjlr7v_tK9dYB9rKIb_K41xhVhVaWca5ZOXOsQ==&uniplatform=NZKPT&language=CHS

summary:
  物理化学I课程知识点多、内容理论性强，概念抽象难以理解，公式多、推导复杂，知识点之间的关联性、逻辑性强，任课教师和学生普遍反映教与学都存在较大难度。知识图谱是一种结构化的语义知识库，它可以系统化、网络化、可视化展示物理化学I课程的知识点及其间的内在关联，以满足碎片化学习背景下学生个性化学习的需求；将其引入物理化学I课程建设过程，可极大地提高教师的教与学生的学的效果。本文结合任课教师团队亲身经历，简要介绍了物理化学I课程知识图谱搭建的过程。

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author: 周思俊;张昊;王国明
date: 2025年19期
keywords: 知识图谱;知识图谱构建;知识推理;深度学习;应用框架
quote: 0
source: 《电脑知识与技术》
site: 万方
title: 知识图谱研究综述
created_at: 2025-09-15 11:08:15.269552
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISGWRuenN5anMtaXRyenlrc2IyMDI1MTkwMTAaCGU3ZGc1M2I1

summary:
  随着信息时代数据量的爆炸性增长,传统知识库已难以满足目前的数据存储需求.知识图谱通过整合多元数据并以结构化方式展现,能有效应对大数据挑战,因此成为人工智能领域的研究热点.文章首先概述知识图谱的基础理论,其次从三个关键环节探讨构建知识图谱的技术细节及模型优劣,在此基础上提出一套系统的技术路径,最后通过提出两个应用框架凸显知识图谱在实际应用中的优势.文章旨在帮助研究者掌握知识图谱的关键技术,为推动知识图谱的发展提供坚实的理论基础.

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author: 李雯昕;昝红英;关同峰
date: 2025年3期
keywords: 知识图谱;命名实体识别;关系抽取;期货文本
quote: 0
source: 《中文信息学报》
site: 万方
title: 期货领域知识图谱构建
created_at: 2025-09-15 11:08:15.269989
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISD3p3eHh4YjIwMjUwMzAwMhoIZTdkZzUzYjU%3D

summary:
  期货领域是数据最丰富的领域之一,该文以商品期货的研究报告为数据来源构建了期货领域知识图谱(Commodity Futures Knowledge Graph,CFKG).以期货产品为核心,确立了概念分类体系及关系描述体系,形成图谱的概念层;在MHS-BIA与GPN模型的基础上,通过领域专家指导对242万字的研报文本进行标注与校对,形成了CFKG数据层,并设计了可视化查询系统.该文所构建的CFKG包含17 003个农产品期货关系三元组、13703种非农产品期货关系三元组,为期货领域文本分析、舆情监控和推理决策等应用提供知识支持.

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author: 石栖;陈文杰;胡正银
date: 2025年3期
keywords: 科学实验;事件知识图谱;知识发现;大语言模型
quote: 2
source: 《数据分析与知识发现》
site: 万方
title: 面向知识发现的科学实验知识图谱构建研究
created_at: 2025-09-15 11:08:15.270472
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISEXhkdHNxYmpzMjAyNTAzMDAxGghlN2RnNTNiNQ%3D%3D

summary:
  [目的]从科技文献中高效挖掘科学实验知识与数据,构建科学实验知识图谱,为知识发现提供高质量数据支撑.[方法]利用事件知识图谱技术对科学实验的复杂性、时序性及知识和数据融合性等知识对象进行统一的知识表示与建模,构建科学实验知识图谱模式层;利用大语言模型提升科学实验知识图谱数据层的知识抽取效率,并以有机太阳能电池为例进行实证.[结果]采用人工标注与大语言模型微调方式构建了一个有机太阳能电池领域科学实验知识图谱,包含34类节点,9种关系,总计有24 348个节点和123 642个关系.[局限]数据来源仅包括论文和专利;科学实验知识图谱构建需要较多专家人工参与,效率尚待进一步提高;未考虑细分领域中的细粒度研究规程和研究方法检验规则等.[结论]本文提出的学科领域科学实验知识图谱构建方法可为实验方案推荐、科学实验演化分析、AI for Science等提供高质量数据支持,有效支撑各类知识发现场景.

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author: 陈强;张栋;李寿山
date: 2025年4期
keywords: 知识图谱补全;多模态;知识融合;多模态融合
quote: 0
source: 《软件学报》
site: 万方
title: 融合任务知识的多模态知识图谱补全
created_at: 2025-09-15 11:08:15.270947
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDXJqeGIyMDI1MDQwMDgaCGU3ZGc1M2I1

summary:
  知识图谱补全任务旨在根据已有的事实三元组(头实体、关系、尾实体)来挖掘知识图谱中缺失的事实三元组.现有的研究工作主要致力于利用知识图谱中的结构信息来进行知识图谱补全任务.然而,这些工作忽略了知识图谱中蕴含的其他模态的信息也可能对知识图谱补全有帮助.并且,由于基于特定任务的知识通常没有被注入通用的预训练模型,因而如何在抽取模态信息的过程中融合任务的相关知识变得至关重要.此外,因为不同模态特征对于知识图谱补全的贡献不一样,所以如何有效地保留有用的多模态信息也是一大挑战.为了解决上述问题,提出一种融合任务知识的多模态知识图谱补全方法.利用在当前任务上微调过的多模态编码器,来获取不同模态下的实体向量表示.并且,通过一个基于循环神经网络的模态融合过滤模块,去除与任务无关的多模态特征.最后,利用同构图网络表征并更新所有特征,从而有效地完成多模态知识图谱补全任务.实验结果表明,所提出的方法能有效地抽取不同模态的信息,并且能够通过进一步的多模态过滤融合来增强实体的表征能力,进而提高多模态知识图谱补全任务的性能.

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author: 赵珂;段林伶;李洁莲
date: 2025年2期
keywords: DIKW模型;知识图谱技术;智慧城市规划;知识表示;知识计算;可解释性推理
quote: 0
source: 《国际城市规划》
site: 万方
title: 知识图谱技术支持
created_at: 2025-09-15 11:08:15.271420
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISD2d3Y3NnaDIwMjUwMjAxNBoIZTdkZzUzYjU%3D

summary:
  以大数据、机器学习应用为主的智慧城市规划仅限于描述城市现象和表象问题是什么、怎么样以及"黑箱"式计算,无法揭示方案生成原因(为什么).受"数据—信息—知识—智慧"金字塔层次DIKW模型的启示,本文引入知识图谱技术,剖析其中知识表示和知识计算两大核心技术对城市规划智慧生成的原理和决策方式的引导,总结出由"建设基础本体集—建立规划方案推理本体—智慧推演规划方案—智慧决策支持规划调整"构成的全生命周期智慧城市规划的知识图谱技术方法和推进路径,赋予城市规划具有"知道为什么"的智慧决策支持能力.

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author: 陆海洋;柳先辉;侯文龙
date: 2025年3期
keywords: 负采样;知识图谱;推荐系统;正混合
quote: 0
source: 《计算机科学》
site: 万方
title: 融合知识图谱的负采样方法
created_at: 2025-09-15 11:08:15.271899
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISDmpzamt4MjAyNTAzMDE5GghlN2RnNTNiNQ%3D%3D

summary:
  为了解决信息过载的问题,推荐系统被广泛研究.由于很难获取大量高质量的显式反馈数据,隐式反馈数据成为训练推荐系统的主流选择.从未标记的数据中采样负例,即负采样,对于训练基于隐式反馈的推荐模型非常重要.现有推荐系统的负采样方法往往只关注如何选择包含更多用户偏好信息的强负样例,却没有考虑强负样例的假阴性问题.为了降低采样得到的负样例的假阴性概率并提高其信息量,提出了一种融合知识图谱的负采样方法.首先,根据用户-项目知识图谱构建负样例候选集;然后,通过基于贝叶斯分类的方式从候选集中筛选假阴性概率最小的负样例;最后,基于Mixup策略引入正混合技术构建强负样例.为了验证所提出方法的有效性,在两个公开数据集上进行了实验.结果表明,与现有方法相比,所提方法表现更优.

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author: 叶志鸿;吴运兵;戴思翀
date: 2025年3期
keywords: 知识图谱补全;多模态融合;本体信息;结构信息;决策学习
quote: 0
source: 《计算机科学与探索》
site: 万方
title: 多级融合知识图谱补全模型
created_at: 2025-09-15 11:08:15.272366
original_link:
  https://d.wanfangdata.com.cn/periodical/ChVQZXJpb2RpY2FsQ0hJMjAyNTA2MjISEWpzamt4eXRzMjAyNTAzMDEzGghlN2RnNTNiNQ%3D%3D

summary:
  知识图谱补全旨在通过预测缺失的三元组来扩展和完善知识图谱,多模态知识图谱补全融合了实体的本体信息,如实体描述、实体图像和实体属性,以获取更精确的实体表示.现有研究将不同模态投影到统一的空间中,以获取实体模态联合表示,再融合知识图谱结构信息作出预测.然而,现存方法融合多模态信息时难以捕捉实体背景知识的复杂交互,不可避免地存在信息丢失和特征提取能力不足的问题;同时过拟合及实体关系交互不足限制了二维卷积模型性能,导致难以融合知识图谱结构信息.因此,提出了多级融合知识图谱补全模型,从实体多模态信息融合与知识图谱结构信息融合两方面解决上述问题.为充分融合实体多模态信息,提出同时使用三种不同融合方法,以全面捕捉实体背景知识交互,并联合决策学习,旨在结合不同多模态融合方法提供的互补信息,以获取实体丰富多样的表示;为充分融合知识图谱结构信息,利用特征泛化来缓解二维卷积模型的过拟合问题,并结合特征重塑增强实体与关系间交互,以提升实体与关系间的上下文感知能力.实验结果表明,该模型在多个公开数据集上均取得较好性能.

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