检索结果-内蒙古大学图书馆

2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion

作者： Mauder, Tomáš Kudela, Jakub Klimeš, Lubomír Zálešák, Martin Charvát, Pavel Energy Institute Brno University of Technology Brno Czech Republic Institute of Automation and Computer Science Brno University of Technology Brno Czech Republic

ISBN: (纸本)9798400704956

This Hot Off the Press paper summarizes our recent work "Soft computing methods in the solution of an inverse heat transfer problem with phase change: A comparative study"published in Engineering Applications of Artificial Intelligence [5]. In the paper, we study inverse heat transfer problems with phase change, where the boundary heat flux is estimated. Such problems are ill-posed and their solution is challenging. Although there were conventional developed for this problem in the past, they are not well-suited for cases including phase change, as these contain strong non-linearities that bring additional computational difficulties. For such problems, soft computing methods provide a promising approach. Four methods from distinct categories of techniques are applied to this problem and thoroughly compared - the conventional gradient-based method, a fuzzy logic-based method, a population-based meta-heuristic, and a surrogate-assisted method. A reformulation of the problem utilizing dimension reduction and decomposition schemes was developed, bringing extensive computational improvements. The metaheuristic and the surrogate-based methods showed superior performance. Their performance was also rather stable and insensitive to the location of the temperature sensor (the source of data for the inverse estimation). A Zenodo repository with the complete implementation of all considered problems and methods is available1. © 2024 Copyright held by the owner/author(s).

关键词： Fuzzy logic

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous Image Knowledge Driven Visual Perception

引用

IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 255-257页

作者： Lan Yan Wenbo Zheng Fei-Yue Wang IEEE the College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China the School of Computer Science and Artificial Intelligence Wuhan University of TechnologyWuhan 430070China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter is concerned with visual perception closely related to heterogeneous *** the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous image knowledge,i.e.,the domain knowledge associated with specific vision tasks,to better address the corresponding visual perception problems.

关键词： Visual visual knowledge

来源：评论

学校读者我要写书评

暂无评论

Reliable deep learning in anomalous diffusion against out-of-distribution dynamics

NATURE COMPUTATIONAL SCIENCE

引用

NATURE COMPUTATIONAL science 2024年第11期4卷 877-877页

作者： Feng, Xiaochen Sha, Hao Zhang, Yongbing Su, Yaoquan Liu, Shuai Jiang, Yuan Hou, Shangguo Han, Sanyang Ji, Xiangyang School of Computer Science and Technology Harbin Institute of Technology (Shenzhen) Shenzhen China Shenzhen International Graduate School Tsinghua University Shenzhen China Institute of Systems and Physical Biology Shenzhen Bay Laboratory Shenzhen China Department of Automation Tsinghua University Beijing China

Anomalous diffusion plays a crucial rule in understanding molecular-level dynamics by offering valuable insights into molecular interactions, mobility states and the physical properties of systems across both biological and materials sciences. Deep-learning techniques have recently outperformed conventional statistical methods in anomalous diffusion recognition. However, deep-learning networks are typically trained by data with limited distribution, which inevitably fail to recognize unknown diffusion models and misinterpret dynamics when confronted with out-of-distribution (OOD) scenarios. In this work, we present a general framework for evaluating deep-learning-based OOD dynamics-detection methods. We further develop a baseline approach that achieves robust OOD dynamics detection as well as accurate recognition of in-distribution anomalous diffusion. We demonstrate that this method enables a reliable characterization of complex behaviors across a wide range of experimentally diverse systems, including nicotinic acetylcholine receptors in membranes, fluorescent beads in dextran solutions and silver nanoparticles undergoing active endocytosis.

关键词： Silver nanoparticles

来源：评论

学校读者我要写书评

暂无评论

Quality-Relevant Modeling and Monitoring of Industrial Cyber-Physical Systems: The Semi-Supervised Dynamic Latent Variable Models

IEEE Transactions on Industrial Cyber-Physical Systems

引用

IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 39-47页

作者： Zhou, Le Wang, Yaoxin Wu, Yuanqing He, Shenghuang Song, Zhihuan Zhejiang University of Science and Technology Department of Automation and Electrical Engineering Hangzhou310023 China Guangdong University of Technology Department of Automation Guangzhou510006 China Dongguan University of Technology Department of Computer Science and Technology Dongguan523808 China Ningbo Industrial Internet Institute Ningbo315012 China Zhejiang University Department of Control Science and Engineering Hangzhou310027 China

In modern industrial cyber-physical systems, a mass of process variables has been obtained by the high-sampling online sensors. Meanwhile, the key quality indexes are usually obtained infrequently from the laboratory. Hence, these quality variables are with low sampling rate. To avail of the complete process and quality variables with various sampling rates in the dynamic processes, a set of semi-supervised dynamic latent variable models are proposed for dynamic modeling and quality-relevant monitoring. The proposed models have built a unified structure to consider both the auto-correlations and cross-correlations between the process and quality variables with unbalanced sampling sizes. Hence, the feature extraction of the time series data is dynamically adjusted under the guidance of the quality variables. Then, the quality-relevant monitoring schemes are proposed, which is validated by a numerical case and an actual wastewater treatment process. © 2024 IEEE. All rights reserved.

关键词： Indexes Probabilistic logic Kalman filters Noise Cyber-physical systems Analytical models Parameter estimation Time series analysis Process monitoring Numerical models

来源：评论

学校读者我要写书评

暂无评论

Developing Lexicons for Enhanced Sentiment Analysis in Software Engineering:An Innovative Multilingual Approach for Social Media Reviews

引用

computers, Materials & Continua 2024年第5期79卷 2771-2793页

作者： Zohaib Ahmad Khan Yuanqing Xia Ahmed Khan Muhammad Sadiq Mahmood Alam Fuad AAwwad Emad A.A.Ismail School of Automation Beijing Institute of TechnologyBeijing100081China Department of Computer Science and Technology University of Science and Technology BannuKPKBannu28100Pakistan School of Computer Science and Engineering Central South UniversityChangsha410083China Department of Quantitative Analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia

Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significantsource of user-generated content. The development of sentiment lexicons that can support languages other thanEnglish is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existingsentiment analysis systems focus on English, leaving a significant research gap in other languages due to limitedresources and tools. This research aims to address this gap by building a sentiment lexicon for local languages,which is then used with a machine learning algorithm for efficient sentiment analysis. In the first step, a lexiconis developed that includes five languages: Urdu, Roman Urdu, Pashto, Roman Pashto, and English. The sentimentscores from SentiWordNet are associated with each word in the lexicon to produce an effective sentiment score. Inthe second step, a naive Bayesian algorithm is applied to the developed lexicon for efficient sentiment analysis ofRoman Pashto. Both the sentiment lexicon and sentiment analysis steps were evaluated using information retrievalmetrics, with an accuracy score of 0.89 for the sentiment lexicon and 0.83 for the sentiment analysis. The resultsshowcase the potential for improving software engineering tasks related to user feedback analysis and productdevelopment.

关键词： Emotional assessment regional dialects SentiWordNet naive bayesian technique lexicons software engineering user feedback

来源：评论

学校读者我要写书评

暂无评论

Generalized Simultaneous Perturbation Stochastic Approximation with Reduced Estimator Bias 57

Generalized Simultaneous Perturbation Stochastic Approximati...

引用

57th Annual Conference on Information sciences and Systems, CISS 2023

作者： Bhatnagar, Shalabh Prashanth, L.A. Indian Institute of Science Department of Computer Science and Automation Bengaluru India Indian Institute of Technology Madras Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9781665451819

We present in this paper a family of generalized simultaneous perturbation stochastic approximation (G-SPSA) estimators that estimate the gradient of the objective using noisy function measurements, but where the number of function measurements and the form of the gradient estimator is guided by the desired estimator bias. In particular, estimators with more function measurements are seen to result in lower bias. We provide an analysis of convergence of generalized SPSA, and point to possible future directions. © 2023 IEEE.

关键词： Approximation theory

来源：评论

学校读者我要写书评

暂无评论

Predefined-time distributed multiobjective optimization for network resource allocation

引用

science China(Information sciences) 2023年第7期66卷 58-72页

作者： Kunpeng ZHANG Lei XU Xinlei YI Zhengtao DING Karl H.JOHANSSON Tianyou CHAI Tao YANG State Key Laboratory of Synthetical Automation for Process Industries Northeastern University School of Electrical Engineering and Computer Science KTH Royal Institute of Technology School of Electrical and Electronic Engineering The University of Manchester

We consider the multiobjective optimization problem for the resource allocation of the multiagent network, where each agent contains multiple conflicting local objective functions. The goal is to find compromise solutions minimizing all local objective functions subject to resource constraints as much as possible, i.e., the Pareto optimums. To this end, we first reformulate the multiobjective optimization problem into one single-objective distributed optimization problem by using the weighted Lppreference index,where the weighting factors of all local objective functions are obtained from the optimization procedure so that the optimizer of the latter is the desired Pareto optimum of the former. Next, we propose novel predefined-time algorithms to solve the reformulated problem by time-based generators. We show that the reformulated problem is solved within a predefined time if the local objective functions are strongly convex and smooth. Moreover, the settling time can be arbitrarily preset since it does not depend on the initial values and designed parameters. Finally, numerical simulations are presented to illustrate the effectiveness of the proposed algorithms.

关键词： distributed optimization multiobjective optimization predefined-time algorithms time-based generators weighted ${L_p}$ preference index

来源：评论

学校读者我要写书评

暂无评论

Hot Off the Press: Benchmarking Derivative-Free Global Optimization Algorithms under Limited Dimensions and Large Evaluation Budgets

Hot Off the Press: Benchmarking Derivative-Free Global Optim...

引用

2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion

作者： Stripinis, Linas Kůdela, Jakub Paulaviçius, Remigijus Institute of Data Science and Digital Technologies Vilnius University Vilnius Lithuania Institute of Automation and Computer Science Brno University of Technology Brno Czech Republic

ISBN: (纸本)9798400704956

This Hot Off the Press paper provides a brief summary of our recent work "Benchmarking Derivative-Free Global Optimization Algorithms under Limited Dimensions and Large Evaluation Budgets"published in IEEE Transactions on Evolutionary Computation [5]. In the paper, we performed a comprehensive computational comparison between stochastic and deterministic global optimization algorithms with twenty-five representative state-of-the-art methods selected from both classes. The experiments were set up with up to twenty dimensions and relatively large evaluation budgets (105 X n). Benchmarking was carried out in a significantly expanded version of the DIRECTGOLib v2.0 library, which included ten distinct collections of primarily continuous test functions. The evaluation of the methods focused on various aspects, such as solution quality, time complexity, and function evaluation usage. The rankings were determined using statistical tests and performance profiles. Our findings suggest that while state-of-the-art deterministic methods could find reasonable solutions with comparatively fewer function evaluations, most stochastic algorithms require more extensive evaluation budgets to deliver comparable results. However, the performance of stochastic algorithms excelled in more complex and higher-dimensional problems. These research findings offer valuable insights for practitioners and researchers, enabling them to tackle diverse optimization problems effectively. © 2024 Copyright held by the owner/author(s).

关键词： Budget control

来源：评论

学校读者我要写书评

暂无评论

Multiple adverse weather removal using adversarial and contrastive learning 9

Multiple adverse weather removal using adversarial and contr...

引用

9th IEEE Smart World Congress, SWC 2023

作者： Zhang, Yuanfan Wang, Jinghua Hu, Liang Harbin Institute of Technology Department of Automation Shenzhen China Harbin Institute of Technology School of Computer Science and Technology Shenzhen China

ISBN: (纸本)9798350319804

Adverse weather removal is significant and valuable for real-world computer vision systems. Most existing algorithms focus on removing one specific type of weather and rely on paired synthesized weather datasets for training. In this paper, to train a multiple weather removal model with unpaired datasets, we introduce multi-dimension contrastive learning mechanism into generative adversarial networks. Specifically, our method consists of two blocks: multi-channel cycle translation (MCCT) block and multi-dimension contrastive learning (MDCL) block. MCCT is used to preserve the color and structural information and gain informative supervisory signals. MDCL is proposed to discriminate feature distribution among different image domains. Results of extensive experiments show that our method is superior over existing unsupervised methods and maintains a decent performance degradation when adapted to multiple weather removal tasks. © 2023 IEEE.

关键词： adverse weather removal contrastive learning deep learning generative adversarial networks unsupervised learning

来源：评论

学校读者我要写书评

暂无评论

Detection of Perfect Stealthy Attacks on Cyber-Physical Systems Subject to Measurement Quantizations: A Watermark-Based Strategy

引用

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 114-125页

作者： Yu-Ang Wang Zidong Wang Lei Zou Bo Shen Hongli Dong the College of Information Science and Technology Donghua University the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of Education IEEE the College of Electrical Engineering and Automation Shandong University of Science and Technology the Department of Computer Science Brunel University London Uxbridge the Sanya Offshore Oil and Gas Research Institute Northeast Petroleum University the Artificial Intelligence Energy Research Institute Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University

In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are quantized before transmission.A specific type of perfect stealthy attack, which meets certain rather stringent conditions, is taken into account. Such attacks could be injected by adversaries into both the sensor-toestimator and controller-to-actuator channels, with the aim of disrupting the normal data flow. For the purpose of defending against these perfect stealthy attacks, a novel scheme based on watermarks is developed. This scheme includes the injection of watermarks(applied to data prior to quantization) and the recovery of data(implemented before the data reaches the estimator).The watermark-based scheme is designed to be both timevarying and hidden from adversaries through incorporating a time-varying and bounded watermark signal. Subsequently, a watermark-based attack detection strategy is proposed which thoroughly considers the characteristics of perfect stealthy attacks,thereby ensuring that an alarm is activated upon the occurrence of such attacks. An example is provided to demonstrate the efficacy of the proposed mechanism for detecting attacks.

关键词： Attack detection cyber-physical systems (CPSs) perfect stealthy attacks watermark-based strategy

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：