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IEEE Transactions on Fuzzy Systems最新文献

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Long-Term Interpretable Air Quality Trend Forecasting via Directed Interval Fuzzy Cognitive Maps 通过定向区间模糊认知图进行可解释的长期空气质量趋势预测
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-10-16 DOI: 10.1109/TFUZZ.2024.3482282
Xiaoqian Liu;Yingjun Zhang;Hui Wang;Sipei Qin;Zhenhua Zhang;Yanyan Yang;Jingping Wang
{"title":"Long-Term Interpretable Air Quality Trend Forecasting via Directed Interval Fuzzy Cognitive Maps","authors":"Xiaoqian Liu;Yingjun Zhang;Hui Wang;Sipei Qin;Zhenhua Zhang;Yanyan Yang;Jingping Wang","doi":"10.1109/TFUZZ.2024.3482282","DOIUrl":"10.1109/TFUZZ.2024.3482282","url":null,"abstract":"Accurate air quality forecasting is crucial for public health and addressing air pollution. However, the dynamic evolution trends, the cross-interference among different air quality indexes, and the error accumulation in the long-term prediction process are still open problems when establishing air quality forecasting models. Thus, we present a long-term interpretable air quality trend forecasting model to address these challenges via directed interval fuzzy cognitive maps, DE-DIFCM. Specifically, we design a time series trend extraction and representation learning module based on the interval fuzzy granules and the Cramer decomposition theorem in the first phase. Next, we formulate the interval information granules' time series forecasting as a DIFCM. In particular, we employ PM\u0000<inline-formula><tex-math>$_{2.5}$</tex-math></inline-formula>\u0000 as a benchmark to validate the performance of the proposed DE-DIFCM. Experimental results on six air quality monitoring datasets demonstrate the model's superior and competitive long-term prediction performance by comparison with some representative baselines.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"32 12","pages":"7129-7142"},"PeriodicalIF":10.7,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443834","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
FGRBC: A Novel Fuzzy Granular Rule-Based Classifier Using the Justifiable Granularity Principle and a Fusion Strategy FGRBC：使用合理粒度原则和融合策略的基于模糊粒度规则的新型分类器
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-10-14 DOI: 10.1109/TFUZZ.2024.3476919
Xiao Zhang;Yijing Liu;Jinhai Li;Changlin Mei
{"title":"FGRBC: A Novel Fuzzy Granular Rule-Based Classifier Using the Justifiable Granularity Principle and a Fusion Strategy","authors":"Xiao Zhang;Yijing Liu;Jinhai Li;Changlin Mei","doi":"10.1109/TFUZZ.2024.3476919","DOIUrl":"10.1109/TFUZZ.2024.3476919","url":null,"abstract":"As a powerful tool for the representation of classifying knowledge, fuzzy classification rules can not only effectively deal with imprecise and uncertain data, but also possess readability and interpretability. Fuzzy granular rules, also to be a kind of fuzzy classification rules, can be induced by fuzzy information granules. It has been acknowledged that one of the important criteria for evaluating the quality of information granules comes from the principle of justifiable granularity. Unfortunately, the existing methods for extracting fuzzy granular rules fail to take into account the principle of justifiable granularity. In view of the advantages of the justifiable granularity principle in classifying knowledge, we propose in this article a new method of extracting fuzzy granular rules using the justifiable granularity principle and a fusion strategy and establish a fuzzy granular rule-based classifier (FGRBC). Specifically, the justifiability of fuzzy granules is first presented according to both coverage and specificity of fuzzy granules, on which a rule extraction method is formulated to obtain a set of fuzzy granular rules. Furthermore, a fusion strategy is put forward to generate a set of fused rules. Then, the two sets of rules are combined and attribute reduction is performed on the combined rule set. Finally, the reduced combined rule set is employed to construct FGRBC. Moreover, performance of FGRBC is evaluated by numerical experiments and the results show that FGRBC is of satisfactory classification ability.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"32 12","pages":"7096-7108"},"PeriodicalIF":10.7,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439749","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
Skeleton-based Gait Recognition Based on Deep Neuro-Fuzzy Network 基于深度神经模糊网络的骨架步态识别技术
IF 11.9 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-10-10 DOI: 10.1109/tfuzz.2024.3444489
Jiefan Qiu, Yizhe Jia, Xingyu Chen, Xiangyun Zhao, Hailin Feng, Kai Fang
{"title":"Skeleton-based Gait Recognition Based on Deep Neuro-Fuzzy Network","authors":"Jiefan Qiu, Yizhe Jia, Xingyu Chen, Xiangyun Zhao, Hailin Feng, Kai Fang","doi":"10.1109/tfuzz.2024.3444489","DOIUrl":"https://doi.org/10.1109/tfuzz.2024.3444489","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"27 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142405356","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
A New Family of Metrics in Interval Space and Their Applications to Multicriteria Decision-Making Theory 区间空间新度量族及其在多标准决策理论中的应用
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-10-10 DOI: 10.1109/TFUZZ.2024.3478827
Y. Chalco-Cano;T. M. Costa;Benjamín Bedregal;Ademir G. Chalco Cano
{"title":"A New Family of Metrics in Interval Space and Their Applications to Multicriteria Decision-Making Theory","authors":"Y. Chalco-Cano;T. M. Costa;Benjamín Bedregal;Ademir G. Chalco Cano","doi":"10.1109/TFUZZ.2024.3478827","DOIUrl":"10.1109/TFUZZ.2024.3478827","url":null,"abstract":"In this article, we analyze the properties of automorphisms in \u0000<inline-formula><tex-math>$mathbb {R}^{2}$</tex-math></inline-formula>\u0000. Then, we consider a subclass of these automorphisms which generate a preference order relation and asymmetric distances between bounded and closed intervals. Symmetrizing these distances, we generate a new family of metrics in this space of intervals which depends on the automorphisms. We study its properties and give a characterization that allows us to calculate the distance between intervals in a simple way. We provide many examples to illustrate our results as well as an application in multicriteria decision-making methods with interval data.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"32 12","pages":"7086-7095"},"PeriodicalIF":10.7,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142405357","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 Bipartite Consensus of Stochastic Multiagent Systems: A Singularity-Free Prescribed Performance Control Approach 随机多代理系统的模糊自适应两方共识：一种无奇点规定性能控制方法
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-10-09 DOI: 10.1109/TFUZZ.2024.3477931
Lei Chen;Hongjing Liang;Yuhua Cheng;Tingwen Huang
{"title":"Fuzzy Adaptive Bipartite Consensus of Stochastic Multiagent Systems: A Singularity-Free Prescribed Performance Control Approach","authors":"Lei Chen;Hongjing Liang;Yuhua Cheng;Tingwen Huang","doi":"10.1109/TFUZZ.2024.3477931","DOIUrl":"10.1109/TFUZZ.2024.3477931","url":null,"abstract":"This article explores the fuzzy adaptive bipartite consensus problem of stochastic multiagent systems (MASs) using a singularity-free prescribed performance control (PPC) approach. When bipartite consensus errors approach constraint boundaries under the effect of adverse factors, the conventional PPC method may encounter a singularity issue, which can degrade system performance or lead to system instability. To address this issue, this article generalizes the concept of shear mapping to the PPC approach of stochastic MASs. Subsequently, a reference performance function is designed to guide the evolution trend of bipartite consensus errors, which effectively decreases the overshoot of bipartite consensus errors. Moreover, a scaling function is designed to remove the feasibility conditions in the existing PPC results. The proposed approach ensures that all signals of the closed-loop systems are semiglobally ultimately uniformly bounded in probability. Finally, a set of simulation results is provided to confirm the effectiveness of the proposed approach.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"32 12","pages":"7073-7085"},"PeriodicalIF":10.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397786","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
Content and Relation Fuzzy Mitigation Framework for Intent Perception 意图感知的内容和关系模糊缓解框架
IF 11.9 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-10-09 DOI: 10.1109/tfuzz.2024.3476948
Wenxin Zhang, Hao Qi, Shutong Wang, Ziqi Lin, Binglu Wang
{"title":"Content and Relation Fuzzy Mitigation Framework for Intent Perception","authors":"Wenxin Zhang, Hao Qi, Shutong Wang, Ziqi Lin, Binglu Wang","doi":"10.1109/tfuzz.2024.3476948","DOIUrl":"https://doi.org/10.1109/tfuzz.2024.3476948","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"70 1","pages":""},"PeriodicalIF":11.9,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397787","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
A Novel Unsupervised Capacity Identification Approach to Deal With Redundant Criteria in Multicriteria Decision Making Problems 处理多标准决策问题中冗余标准的新型无监督能力识别方法
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-10-09 DOI: 10.1109/TFUZZ.2024.3476484
Guilherme Dean Pelegrina;Leonardo Tomazeli Duarte
{"title":"A Novel Unsupervised Capacity Identification Approach to Deal With Redundant Criteria in Multicriteria Decision Making Problems","authors":"Guilherme Dean Pelegrina;Leonardo Tomazeli Duarte","doi":"10.1109/TFUZZ.2024.3476484","DOIUrl":"10.1109/TFUZZ.2024.3476484","url":null,"abstract":"The use of the Choquet integral in multicriteria decision making problems has gained attention in the last two decades. Despite of its usefulness, there is the issue of how to define the Choquet integral parameters, called capacity coefficients, specially the ones associated with coalitions of criteria. A possible approach to address this issue is based on unsupervised learning, which aims to define such parameters with the goal of mitigating undesirable effects provided by intercriteria relations. However, current unsupervised approaches present some drawbacks, as there is no guarantee that the parameters are equally prioritized in the learning procedure. In this article, we propose a novel unsupervised capacity identification approach which ensures a fair learning for all parameters. Moreover, in comparison with the existing methods, our proposal is less complex in terms of optimization, as it is based on a linear formulation. Experimental results in both synthetic and real datasets attest the applicability of our proposal.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"32 12","pages":"7196-7201"},"PeriodicalIF":10.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397788","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 Guaranteed Cost Event-Triggered-Based Anti-Disturbance Control of T-S Fuzzy Wind-Turbine Systems Subject to External Disturbances 受外部扰动影响的 T-S 模糊风力涡轮机系统的基于事件触发的动态保证成本抗扰动控制
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-10-08 DOI: 10.1109/TFUZZ.2024.3476320
Yang Gu;Mouquan Shen;Ju H. Park;Qing-Guo Wang;Zheng Hong Zhu
{"title":"Dynamic Guaranteed Cost Event-Triggered-Based Anti-Disturbance Control of T-S Fuzzy Wind-Turbine Systems Subject to External Disturbances","authors":"Yang Gu;Mouquan Shen;Ju H. Park;Qing-Guo Wang;Zheng Hong Zhu","doi":"10.1109/TFUZZ.2024.3476320","DOIUrl":"10.1109/TFUZZ.2024.3476320","url":null,"abstract":"In this article, we investigate an improved dynamic guaranteed cost event-triggered-based anti-disturbance control for Takagi–Sugeno fuzzy wind-turbine systems subject to external disturbances. A guaranteed cost event-triggered paradigm with dynamic threshold and sector structure is constructed to alleviate unnecessary triggers caused by outlier measurement. An additional event condition is designed to deal with the difference of premise variable between the system and controller. A PI-type intermediate estimator is introduced to simultaneously estimate the system state and external disturbance. Subsequently, an event-triggered fuzzy controller is built to actively compensate the external disturbances. With the help of Finsler's lemma, sufficient criteria are derived in terms of linear matrix inequalities to make the wind-turbine systems asymptotically stable. Finally, the proposed method is verified by comparative studies.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"32 12","pages":"7063-7072"},"PeriodicalIF":10.7,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142385439","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
Adaptive Fuzzy Predefined-Time Tracking Control Design for Nonstrict-Feedback High-Order Nonlinear Systems With Input Quantization 带输入量化的非严格反馈高阶非线性系统的自适应模糊预定义时间跟踪控制设计
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-10-07 DOI: 10.1109/TFUZZ.2024.3431047
Shuai Sui;Lin Zhao;C. L. Philip Chen
{"title":"Adaptive Fuzzy Predefined-Time Tracking Control Design for Nonstrict-Feedback High-Order Nonlinear Systems With Input Quantization","authors":"Shuai Sui;Lin Zhao;C. L. Philip Chen","doi":"10.1109/TFUZZ.2024.3431047","DOIUrl":"10.1109/TFUZZ.2024.3431047","url":null,"abstract":"This article studies the problem of an adaptive fuzzy predefined-time tracking control approach for a type of uncertain nonstrict-feedback high-order nonlinear systems with input quantization. The considered plants contain unknown nonlinear functions, input quantization, and external disturbances. Based on the backstepping recursive technique and predefined-time stability criterion, a fuzzy adaptive predefined-time control strategy is presented. To address the difficulties posed by the uncertain nonlinearities within the original systems, the fuzzy logic systems are incorporated into estimate the unknown nonlinear functions, while power integrator technology is used to overcome the hurdle presented by high-order terms. Using the predefined-time Lyapunov stability theory, the system stability analysis is provided, and it is proved that all signals in the closed-loop system are bounded within the preset time interval. Ultimately, the effectiveness of the presented control approach is corroborated through numerical simulation.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"32 10","pages":"5978-5990"},"PeriodicalIF":10.7,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142384252","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
IEEE Transactions on Fuzzy Systems Publication Information IEEE Transactions on Fuzzy Systems 出版信息
IF 10.7 1区 计算机科学
IEEE Transactions on Fuzzy Systems Pub Date : 2024-10-07 DOI: 10.1109/TFUZZ.2024.3463851
{"title":"IEEE Transactions on Fuzzy Systems Publication Information","authors":"","doi":"10.1109/TFUZZ.2024.3463851","DOIUrl":"10.1109/TFUZZ.2024.3463851","url":null,"abstract":"","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"32 10","pages":"C2-C2"},"PeriodicalIF":10.7,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10707044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142384353","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
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