IEEE Transactions on Fuzzy Systems最新文献_第9页

Input Importance Analysis for a Class of Incremental Hierarchical Fuzzy Systems—Theory and Experiments 一类增量式层次模糊系统的输入重要性分析——理论与实验

IF 11.9 1区计算机科学

IEEE Transactions on Fuzzy Systems Pub Date : 2025-07-14 DOI: 10.1109/TFUZZ.2025.3588624

Jianjian Zhao;Jiayu Zhao;Hainan Yang;Tao Zhao

{"title":"Input Importance Analysis for a Class of Incremental Hierarchical Fuzzy Systems—Theory and Experiments","authors":"Jianjian Zhao;Jiayu Zhao;Hainan Yang;Tao Zhao","doi":"10.1109/TFUZZ.2025.3588624","DOIUrl":"10.1109/TFUZZ.2025.3588624","url":null,"abstract":"Hierarchical fuzzy systems (HFSs), as a type of deep-structured fuzzy model, exhibit strong expressive power, excellent scalability, high flexibility, and desirable interpretability, making them highly promising for tackling a variety of complex problems. Despite their widespread applications in various fields such as control, classification, and modeling, very little research has been conducted to analyze how inputs influence the system’s behavior. Consequently, this article presents an in-depth analysis of a class of incremental HFSs (IHFSs) from two perspectives of input importance. First, an enhanced mutual information-based input importance ranking method is proposed, enabling a more effective and concise evaluation of the degree to which inputs influence or depend on the ground truth. Next, a comprehensive sensitivity analysis, both at the subsystem level and the entire system level, is performed to illustrate the impact of inputs on the system. Specifically, a novel sensitivity metric, termed average sensitivity (AS), is proposed to simplify sensitivity calculations, thereby significantly reducing computational costs. Several related theorems are provided to theoretically analyze the sensitivity of the system to inputs under specific conditions. Furthermore, an evaluation framework based on the AS, called ASEF, is proposed for assessing the rationality of the constructed IHFS structure, which facilitates the effective design of high-performance systems for modeling tasks. A series of experiments on both synthetic and real-world datasets demonstrate the effectiveness and superiority of the proposed methods. Finally, several potential research directions are suggested to drive further progress.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 9","pages":"3281-3296"},"PeriodicalIF":11.9,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144630012","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

Switching Event-Triggered Protocol for Fuzzy Singularly Perturbed Systems Under Random Sampling Periods 随机采样周期下模糊奇摄动系统的交换事件触发协议

IF 11.9 1区计算机科学

IEEE Transactions on Fuzzy Systems Pub Date : 2025-07-14 DOI: 10.1109/TFUZZ.2025.3588756

Jun Cheng;Jianlin Bai;Mengzhuo Luo;Michael Basin;Zhiguo Yan;Huaicheng Yan

引用次数: 0

Hypergraph Community Detection With Fuzzy Memberships 具有模糊隶属关系的超图社区检测

IF 11.9 1区计算机科学

IEEE Transactions on Fuzzy Systems Pub Date : 2025-07-14 DOI: 10.1109/TFUZZ.2025.3588125

Jing Xiao;Zhi-Wei Ma;Jing Cao;Xiao-Ke Xu

{"title":"Hypergraph Community Detection With Fuzzy Memberships","authors":"Jing Xiao;Zhi-Wei Ma;Jing Cao;Xiao-Ke Xu","doi":"10.1109/TFUZZ.2025.3588125","DOIUrl":"10.1109/TFUZZ.2025.3588125","url":null,"abstract":"Hypergraph community detection reveals both mesoscale structures and functional characteristics of real-life hypergraphs. Although many methods have been developed from diverse perspectives, to our knowledge, none can provide fine-grained hypergraph fuzzy community information, and the quality of identified crisp partitions is often limited. This study defines a set of novel concepts of multi-scale hypergraph fuzzy memberships that systematically quantify the partial belongingness (i.e., membership grades) among nodes, hyperedges, and hypergraph communities within the interval [0,1], thereby revealing the multi-scale partial topological affiliations. Furthermore, the multiscale hypergraph fuzzy memberships are employed to develop a general framework, named fuzzy membership-assisted hypergraph modularity optimization (FMHMO), aiming to approximate the modularity-optimal crisp hypergraph partition. The FMHMO framework comprises two key strategies: Hyperedge similarity-based hypergraph reduction (HS-HR) and fuzzy membership-based hypergraph partition recovery (FM-HPR). In particular, HS-HR reduces a hypergraph to a simple weighted graph, mapping hyperedges as nodes and their interactions as edges using novel hyperedge similarity as weights. Thereby, preserving intrahyperedge and interhyperedge topologies of the original hypergraph. FM-HPR recovers a hypergraph partition from the approximately modularity-optimal weighted graph partition by quantifying the fuzzy memberships of bridge nodes connecting multiple incident hyperedges, thereby enabling precise assignment of their crisp hypergraph community affiliations. Experimental results in both synthetic and real-world datasets indicate the superiority of FMHMO over state-of-the-art hypergraph community detection algorithms in accuracy and modularity quality.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 9","pages":"3253-3266"},"PeriodicalIF":11.9,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144630014","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

Multi-Agent Fuzzy Reinforcement Learning With LLM for Cooperative Navigation of Endovascular Robotics 基于LLM的多智能体模糊强化学习血管内机器人协同导航

IF 11.9 1区计算机科学

IEEE Transactions on Fuzzy Systems Pub Date : 2025-07-14 DOI: 10.1109/tfuzz.2025.3585934

Tianliang Yao, Yueqi Xu, Haoyu Wang, Xihe Qiu, Kaspar Althoefer, Peng Qi

引用次数: 0

Fixed-Time Multi-Almost-Periodicity in Switched Fuzzy Neural Networks With Multicontroller Strategies 多控制器策略下切换模糊神经网络的定时多近周期性

IF 11.9 1区计算机科学

IEEE Transactions on Fuzzy Systems Pub Date : 2025-07-03 DOI: 10.1109/TFUZZ.2025.3585694

Shiqin Ou;Zhenyuan Guo;Xiaobing Nie;Shiping Wen;Tingwen Huang

{"title":"Fixed-Time Multi-Almost-Periodicity in Switched Fuzzy Neural Networks With Multicontroller Strategies","authors":"Shiqin Ou;Zhenyuan Guo;Xiaobing Nie;Shiping Wen;Tingwen Huang","doi":"10.1109/TFUZZ.2025.3585694","DOIUrl":"10.1109/TFUZZ.2025.3585694","url":null,"abstract":"This article provides theoretical analysis of the fixed-time multi-almost-periodicity in switched fuzzy neural networks, employing multicontroller strategies and a state-dependent switching mechanism. Utilizing the Ascoli–Arzela theorem, the properties of <inline-formula><tex-math>$M$</tex-math></inline-formula>-matrix, Lyapunov functions method, and some inequality techniques, we establish some sufficient conditions to ascertain that the number of exponentially stable almost-periodic solutions can be up to <inline-formula><tex-math>$4^{n}$</tex-math></inline-formula>, where <inline-formula><tex-math>$n$</tex-math></inline-formula> is the number of neurons. Furthermore, we design various controllers to achieve the fixed-time stability for various almost-periodic solutions located in the positive invariant sets. Then, the settling time for the switched fuzzy networks to achieve multi-almost-periodicity is estimated. It is noteworthy to state that this article considers fixed-time multiperiodicity and fixed-time multistability as special cases of fixed-time multi-almost-periodicity. Two numerical examples are presented to demonstrate the theoretical results.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 9","pages":"3210-3224"},"PeriodicalIF":11.9,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144566108","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

One-Step Fuzzy Ensemble Clustering Method via Embedding Ground-Truth Cluster Number Graphs 基于嵌入真值聚类图的一步模糊集成聚类方法

IF 11.9 1区计算机科学

IEEE Transactions on Fuzzy Systems Pub Date : 2025-07-03 DOI: 10.1109/TFUZZ.2025.3585929

Zekang Bian;Jia Qu;Zhaohong Deng;Shitong Wang

{"title":"One-Step Fuzzy Ensemble Clustering Method via Embedding Ground-Truth Cluster Number Graphs","authors":"Zekang Bian;Jia Qu;Zhaohong Deng;Shitong Wang","doi":"10.1109/TFUZZ.2025.3585929","DOIUrl":"10.1109/TFUZZ.2025.3585929","url":null,"abstract":"In multisource clustering tasks, the number of clusters in each source or view may not align with the number of ground-truth clusters. Existing ensemble clustering methods face two notable challenges: 1) developing a new ensemble framework that yields a final clustering result matching the ground-truth cluster count and 2) revealing consistency among all base clustering results. To address these challenges, we propose a novel one-step fuzzy ensemble clustering method (OS-FECM) that incorporates ground-truth cluster number graphs. Initially, OS-FECM establishes a one-step fuzzy ensemble framework that directly integrates all base fuzzy clustering results (i.e., membership matrices) with varying cluster counts, thereby eliminating reliance on the coassociation matrix typical of existing two-step ensemble frameworks. Furthermore, we construct a ground-truth cluster number graph, which maps the number of clusters in each base clustering result to the ground-truth cluster count in the final ensemble result. This graph reveals the consistency among all base fuzzy clustering results and illustrates the relationships between clusters in the base results and the ground-truth clusters. It is then embedded into the corresponding base fuzzy clustering results to enhance the final ensemble result. Finally, we employ an alternating optimization method alongside a weighting mechanism to derive the final ensemble clustering result and adaptively assign importance to each base clustering result. Experimental evaluations across various datasets demonstrate that OS-FECM achieves clustering performance that is at least comparable to, if not superior to, that of other comparative methods.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 9","pages":"3225-3239"},"PeriodicalIF":11.9,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565908","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 Computational Intelligence Society Information IEEE计算智能学会信息

IF 10.7 1区计算机科学

IEEE Transactions on Fuzzy Systems Pub Date : 2025-07-02 DOI: 10.1109/TFUZZ.2025.3579179

引用次数: 0

Erratum to “Spatial Weighted Robust Clustering of Multivariate Time Series Based on Quantile Dependence With an Application to Mobility During COVID-19 Pandemic” “基于分位数相关性的多变量时间序列空间加权鲁棒聚类及其在COVID-19大流行期间流动性中的应用”的勘误

IF 10.7 1区计算机科学

IEEE Transactions on Fuzzy Systems Pub Date : 2025-07-02 DOI: 10.1109/TFUZZ.2025.3567172

Ángel López-Oriona;Pierpaolo D'Urso;José A. Vilar;Borja Lafuente-Rego

引用次数: 0

IEEE Transactions on Fuzzy Systems Publication Information IEEE模糊系统学报

IF 10.7 1区计算机科学

IEEE Transactions on Fuzzy Systems Pub Date : 2025-07-02 DOI: 10.1109/TFUZZ.2025.3579177

引用次数: 0

Event-Based Fuzzy Asynchronous Consensus for UAV Swarm Under Jointly Connected Digraphs 联合连通有向图下基于事件的无人机群模糊异步一致性

IF 11.9 1区计算机科学

IEEE Transactions on Fuzzy Systems Pub Date : 2025-07-01 DOI: 10.1109/TFUZZ.2025.3585162

Yuyuan Shi;Jing Li;Maolong Lv;Ning Wang

{"title":"Event-Based Fuzzy Asynchronous Consensus for UAV Swarm Under Jointly Connected Digraphs","authors":"Yuyuan Shi;Jing Li;Maolong Lv;Ning Wang","doi":"10.1109/TFUZZ.2025.3585162","DOIUrl":"10.1109/TFUZZ.2025.3585162","url":null,"abstract":"An adaptive fuzzy dynamic event-triggered control approach is proposed for a fleet of fixed-wing unmanned aerial vehicles (UAVs) operating under jointly connected switching topologies. The primary challenge lies in addressing asynchronous switching topologies caused by topology identification delays. To tackle this, asynchronous distributed observers are constructed, and topological switching rules are designed, ensuring that all follower UAVs can estimate the leader UAV’s state by leveraging asynchronous distributed state errors. In addition, a novel dynamic event-triggering mechanism is introduced. Compared to state-of-the-art methods, the proposed triggering function directly couples the external state variable with the last triggered value, dynamically regulates the triggered interval based on the control performance, and minimizes the number of occurrences while maintaining the system performance. An adaptive fuzzy translational and rotational controller is further developed to enable the follower UAVs to accurately track the state of the leader UAV while ensuring that all closed-loop states remain globally uniformly ultimately bounded. The proposed strategies are validated for effectiveness and superiority through a semiphysical simulation platform.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"33 9","pages":"3195-3209"},"PeriodicalIF":11.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144533133","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