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IEEE Transactions on Fuzzy Systems最新文献

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Fuzzy Terminal Sliding-mode Control with Adaptive Switching Gain 自适应开关增益模糊终端滑模控制
IF 11.9 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2025-01-07 DOI: 10.1109/tfuzz.2025.3526784
Cheng-Cheng Feng, Hao-Yuan Sun, Hong-Gui Han, Sheng-Li Du
{"title":"Fuzzy Terminal Sliding-mode Control with Adaptive Switching Gain","authors":"Cheng-Cheng Feng, Hao-Yuan Sun, Hong-Gui Han, Sheng-Li Du","doi":"10.1109/tfuzz.2025.3526784","DOIUrl":"https://doi.org/10.1109/tfuzz.2025.3526784","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"100 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142936047","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
Distributed Adaptive Tracking Control for Fuzzy Nonlinear MASs Under Round-Robin Protocol 轮循协议下模糊非线性质量的分布式自适应跟踪控制
IF 11.9 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2025-01-06 DOI: 10.1109/tfuzz.2025.3525989
Sha Fan, Min Meng, Yukai Fu, Chao Deng
{"title":"Distributed Adaptive Tracking Control for Fuzzy Nonlinear MASs Under Round-Robin Protocol","authors":"Sha Fan, Min Meng, Yukai Fu, Chao Deng","doi":"10.1109/tfuzz.2025.3525989","DOIUrl":"https://doi.org/10.1109/tfuzz.2025.3525989","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"25 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142934570","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
Dynamic Fuzzy Sampler for Graph Neural Networks 图神经网络的动态模糊采样器
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2025-01-06 DOI: 10.1109/TFUZZ.2024.3509018
Jia Wei;Xingjun Zhang;Witold Pedrycz;Weiping Ding
{"title":"Dynamic Fuzzy Sampler for Graph Neural Networks","authors":"Jia Wei;Xingjun Zhang;Witold Pedrycz;Weiping Ding","doi":"10.1109/TFUZZ.2024.3509018","DOIUrl":"10.1109/TFUZZ.2024.3509018","url":null,"abstract":"Graph Neural Networks (GNNs) are widely used across fields, with inductive learning replacing transductive learning as the mainstream training paradigm due to its superior memory efficiency, computation speed, and generalization. Neighbor node sampling, a key step in inductive learning, is critical to model performance. However, existing samplers focus only on adjacency matrix-based sampling, neglecting the varying impacts of different neighbors on target nodes over time. They usually aggregate the neighbor information in a simple way such as averaging or summing, which limits the information representation, robustness, and generalization. To address these limitations, we propose a Dynamic Fuzzy Sampler (DFS) based on a Gaussian fuzzy system. DFS accounts for node diversity and models the uncertainties and fuzziness in neighbor-target mutual information dynamically. Specifically, DFS first innovatively constructs a learnable Gaussian fuzzy set system for determining the membership degree of different neighbors to the target node at different moments. Subsequently, DFS aggregates the target node embeddings and membership-weighted neighbor embeddings to update the target node's features, which makes the target node utilize the sampling information more effectively. The aggregated target node effectively captures the graph structure information and neighbor node information, which can facilitate the subsequent graph neural network-based graph representation model with stronger representation and generalization capabilities. Experimental results on supervised and self-supervised graph datasets demonstrate that DFS consistently outperforms state-of-the-art sampling schemes. DFS achieves up to 1.90% and 9.52% F1-score improvement compared to the state-of-the-art schemes on small- and large-scale graphs, respectively.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 4","pages":"1357-1368"},"PeriodicalIF":10.7,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142934629","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
Event-Triggered Trajectory Tracking Control for Unmanned Surface Vessels With Prescribed Performance Using Barrier Lyapunov Functions 基于Barrier Lyapunov函数的规定性能无人水面舰艇事件触发轨迹跟踪控制
IF 11.9 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2025-01-03 DOI: 10.1109/tfuzz.2025.3525701
Xian Du, Xu Yuan, Bin Yang, Xudong Zhao
{"title":"Event-Triggered Trajectory Tracking Control for Unmanned Surface Vessels With Prescribed Performance Using Barrier Lyapunov Functions","authors":"Xian Du, Xu Yuan, Bin Yang, Xudong Zhao","doi":"10.1109/tfuzz.2025.3525701","DOIUrl":"https://doi.org/10.1109/tfuzz.2025.3525701","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"159 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142924716","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
Small-Gain-Based Fixed-Time Faulty Parameter Estimation for the Interconnected Fuzzy Systems With Multiple Time-Varying Delays 多时变时滞互联模糊系统的小增益定时故障参数估计
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2025-01-03 DOI: 10.1109/TFUZZ.2024.3520347
Ke Zhang;Qingyi Liu;Bin Jiang
{"title":"Small-Gain-Based Fixed-Time Faulty Parameter Estimation for the Interconnected Fuzzy Systems With Multiple Time-Varying Delays","authors":"Ke Zhang;Qingyi Liu;Bin Jiang","doi":"10.1109/TFUZZ.2024.3520347","DOIUrl":"10.1109/TFUZZ.2024.3520347","url":null,"abstract":"This article investigates the fixed-time faulty parameter estimation problem for an interconnected fuzzy system with multiple time-varying delays. Based on the persistent excitation condition, an adaptive observer with a faulty parameter identification algorithm is constructed, to provide the accurate information of partial loss of actuator effectiveness within a fixed settling-time, and to guarantee the boundedness of state estimation error by mitigating the influence of external disturbance. Accordingly, several sufficient conditions for the existence of fuzzy observer gain, and the convergence proof of the input-to-state stability are also presented by utilizing the small-gain technique. Afterwards, an active fault-tolerant controller is synthesized to maintain the faulty interconnected system by compensating the actuator fault. Finally, simulation results on an inverted-pendulum system and a numerical example show the feasibility and advantage of the proposed approaches.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 4","pages":"1343-1356"},"PeriodicalIF":10.7,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142924731","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
Secure Control for T-S Fuzzy Wind Turbine Systems Under Hybrid Cyberattacks Via an Adaptive Memory Event-Triggered Mechanism 基于自适应记忆事件触发机制的混合网络攻击下T-S模糊风力发电系统安全控制
IF 11.9 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2025-01-03 DOI: 10.1109/tfuzz.2025.3525778
Dong Xu, Yajuan Liu, Sangmoon Lee
{"title":"Secure Control for T-S Fuzzy Wind Turbine Systems Under Hybrid Cyberattacks Via an Adaptive Memory Event-Triggered Mechanism","authors":"Dong Xu, Yajuan Liu, Sangmoon Lee","doi":"10.1109/tfuzz.2025.3525778","DOIUrl":"https://doi.org/10.1109/tfuzz.2025.3525778","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"8 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142924717","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
Fuzzy Adaptive Group Formation-Containment Tracking Control of Nonlinear Multiagent Systems With Intermittent Actuator Faults 具有间歇执行器故障的非线性多智能体系统的模糊自适应群形成-容纳跟踪控制
IF 11.9 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2025-01-02 DOI: 10.1109/tfuzz.2025.3525481
Zhibin Zhu, Yunbiao Jiang, Zhongxin Liu, Fuyong Wang
{"title":"Fuzzy Adaptive Group Formation-Containment Tracking Control of Nonlinear Multiagent Systems With Intermittent Actuator Faults","authors":"Zhibin Zhu, Yunbiao Jiang, Zhongxin Liu, Fuyong Wang","doi":"10.1109/tfuzz.2025.3525481","DOIUrl":"https://doi.org/10.1109/tfuzz.2025.3525481","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"6 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142917152","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
Fuzzy Quantum Group Decision Making and Its Application in Meteorological Disaster Emergency 模糊量子群决策及其在气象灾害应急中的应用
IF 11.9 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2025-01-02 DOI: 10.1109/tfuzz.2024.3525009
Shuli Yan, Yizhao Xu, Zaiwu Gong, Enrique Herrera-Viedma
{"title":"Fuzzy Quantum Group Decision Making and Its Application in Meteorological Disaster Emergency","authors":"Shuli Yan, Yizhao Xu, Zaiwu Gong, Enrique Herrera-Viedma","doi":"10.1109/tfuzz.2024.3525009","DOIUrl":"https://doi.org/10.1109/tfuzz.2024.3525009","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"72 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142917153","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
Predefined-Time Fuzzy Formation Control for High-Order Multiagent Systems via Event-Triggered Schemes 基于事件触发方案的高阶多智能体系统的预定义时间模糊编队控制
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2025-01-01 DOI: 10.1109/TFUZZ.2024.3524716
Jiawei Ma;Huaguang Zhang;Juan Zhang;Lei Wan
{"title":"Predefined-Time Fuzzy Formation Control for High-Order Multiagent Systems via Event-Triggered Schemes","authors":"Jiawei Ma;Huaguang Zhang;Juan Zhang;Lei Wan","doi":"10.1109/TFUZZ.2024.3524716","DOIUrl":"10.1109/TFUZZ.2024.3524716","url":null,"abstract":"This research considers the predefined-time adaptive fuzzy formation control issue for high-order nonlinear multiagent systems. By applying fuzzy logic systems, the systems unknown nonlinear functions can be approximated. To refrain from “explosion of complexity problem”, a novel dynamics surface for high-order nonlinear multiagent systems is presented. Further, to minimize the communication burden, an event-triggered mechanism suitable for high-order nonlinear multiagent systems is applied in the control methods. With the help of the backstepping design scheme and the adding power integral method, an adaptive fuzzy predefined-time formation control approach is proposed so that all signals in the considered systems are bounded and realize the desired formation control within predefined time. The illustrative examples are presented to verify the validity of the suggested method.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 4","pages":"1333-1342"},"PeriodicalIF":10.7,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142911798","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
Adjacency-aware Fuzzy Label Learning for Skin Disease Diagnosis 邻接感知模糊标签学习用于皮肤病诊断
IF 11.9 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-12-30 DOI: 10.1109/tfuzz.2024.3524250
Murong Zhou, Baifu Zuo, Guohua Wang, Gongning Luo, Fanding Li, Suyu Dong, Wei Wang, Kuanquan Wang, Xiangyu Li, Lifeng Xu
{"title":"Adjacency-aware Fuzzy Label Learning for Skin Disease Diagnosis","authors":"Murong Zhou, Baifu Zuo, Guohua Wang, Gongning Luo, Fanding Li, Suyu Dong, Wei Wang, Kuanquan Wang, Xiangyu Li, Lifeng Xu","doi":"10.1109/tfuzz.2024.3524250","DOIUrl":"https://doi.org/10.1109/tfuzz.2024.3524250","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"1 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905572","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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