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IEEE Transactions on Systems, Man, and Cybernetics: Systems Publication Information IEEE系统、人与控制论汇刊：系统出版信息
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-09-19 DOI: 10.1109/TSMC.2025.3604199
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引用次数: 0
Thank You for Your Authorship 谢谢你的作者
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-09-19 DOI: 10.1109/TSMC.2025.3606176
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引用次数: 0
IEEE Transactions on Systems, Man, and Cybernetics: Systems Information for Authors IEEE系统、人与控制论汇刊：作者的系统信息
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-09-19 DOI: 10.1109/TSMC.2025.3604203
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引用次数: 0
TechRxiv: Share Your Preprint Research With the World! techxiv：与世界分享你的预印本研究！
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-09-19 DOI: 10.1109/TSMC.2025.3604195
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引用次数: 0
IEEE Transactions on Systems, Man, and Cybernetics: Systems Publication Information IEEE系统、人与控制论汇刊：系统出版信息
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-09-19 DOI: 10.1109/TSMC.2025.3604187
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引用次数: 0
IEEE Transactions on Systems, Man, and Cybernetics: Systems Information for Authors IEEE系统、人与控制论汇刊：作者的系统信息
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-09-19 DOI: 10.1109/TSMC.2025.3604211
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引用次数: 0
IEEE Systems, Man, and Cybernetics Society Information IEEE系统、人与控制论学会信息
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-09-19 DOI: 10.1109/TSMC.2025.3604201
{"title":"IEEE Systems, Man, and Cybernetics Society Information","authors":"","doi":"10.1109/TSMC.2025.3604201","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3604201","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"C3-C3"},"PeriodicalIF":8.7,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11173517","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
IEEE Systems, Man, and Cybernetics Society Information IEEE系统、人与控制论学会信息
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-09-19 DOI: 10.1109/TSMC.2025.3604209
{"title":"IEEE Systems, Man, and Cybernetics Society Information","authors":"","doi":"10.1109/TSMC.2025.3604209","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3604209","url":null,"abstract":"","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"C3-C3"},"PeriodicalIF":8.7,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11173423","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Adaptive Neural Network Tracking Control for Nonstrict-Feedback Nonlinear Systems With States and Inputs Quantization 状态和输入量化的非严格反馈非线性系统的自适应神经网络跟踪控制
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-28 DOI: 10.1109/TSMC.2025.3599146
Hang Su;Weihai Zhang
{"title":"Adaptive Neural Network Tracking Control for Nonstrict-Feedback Nonlinear Systems With States and Inputs Quantization","authors":"Hang Su;Weihai Zhang","doi":"10.1109/TSMC.2025.3599146","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3599146","url":null,"abstract":"It is a common control issue that the input signal of the system is quantized in the controller-to-actuator channel via the communication network, but few results are available in considering adaptive tracking control problem for nonstrict-feedback nonlinear system with both state and input quantization. The control problem is figured out in our article by developing an adaptive neural network control method for nonstrict-feedback nonlinear system with quantized input and states. In addition to overcoming the difficulty that the virtual control signal cannot be defined by quantized states in backstepping-based design approach, our work also surmounts the influence of the coexistence of nonstrict-feedback structure and state discontinuity resulted from quantization, and gives the construction of adaptive law for the weight vector of approximation system based on neural network. Elaborate simulation examples are depicted to verify the effectiveness of our depicted quantized control algorithm.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7591-7602"},"PeriodicalIF":8.7,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Distribution Direction-Assisted Two-Stage Knowledge Transfer for Many-Task Optimization 多任务优化的分布方向辅助两阶段知识转移
IF 8.7 1区 计算机科学
IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-08-27 DOI: 10.1109/TSMC.2025.3598800
Tingyu Zhang;Xinyi Wu;Yanchi Li;Wenyin Gong;Hu Qin
{"title":"Distribution Direction-Assisted Two-Stage Knowledge Transfer for Many-Task Optimization","authors":"Tingyu Zhang;Xinyi Wu;Yanchi Li;Wenyin Gong;Hu Qin","doi":"10.1109/TSMC.2025.3598800","DOIUrl":"https://doi.org/10.1109/TSMC.2025.3598800","url":null,"abstract":"Evolutionary many-task optimization (EMaTO) endeavors to solve more than three optimization tasks simultaneously by leveraging similarities among tasks. While existing algorithms have shown promising results, they face significant challenges in low-similarity scenarios. First, existing transfer techniques, which rely on population location and distribution, become ineffective. Second, the difficulty of selecting appropriate knowledge increases significantly. To address these challenges, we introduce a new concept: distribution direction knowledge, i.e., the evolutionary direction (ED) of elite solutions. It enables the target task to learn the search experience of source tasks with similar evolutionary trends. To utilize this knowledge effectively, an EMaTO algorithm with distribution direction-assist two-stage knowledge transfer (DTSKT) is proposed. First, an ED-based multisource selection strategy is proposed to obtain appropriate knowledge in different circumstances. Second, we design a two-stage knowledge transfer (TSKT) strategy to search promising regions, consisting of exploration-oriented and exploitation-oriented knowledge transfer. In addition, to directly obtain distribution direction knowledge, the estimation of distribution algorithm is applied as the basic optimizer, explicitly revealing the ED of populations by employing probability distributions. Afterward, to validate the ability of DTSKT to handle tasks with different similarities, we utilize a test problem generator to create a more challenging many-task benchmark suite, named STOP. The results on the WCCI20 and STOP benchmark suites, along with a real-world application, demonstrate that DTSKT generally outperforms seven state-of-the-art algorithms.","PeriodicalId":48915,"journal":{"name":"IEEE Transactions on Systems Man Cybernetics-Systems","volume":"55 10","pages":"7551-7565"},"PeriodicalIF":8.7,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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