Fuzzy Sets and Systems最新文献_第6页

Fixed-time adaptive fuzzy event-triggered fault-tolerant containment control for nonlinear multi-agent systems 非线性多智能体系统的定时自适应模糊事件触发容错控制

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-04-15 Epub Date: 2025-12-18 DOI: 10.1016/j.fss.2025.109732

Guanglei Zhao , Xianyu Liu

{"title":"Fixed-time adaptive fuzzy event-triggered fault-tolerant containment control for nonlinear multi-agent systems","authors":"Guanglei Zhao , Xianyu Liu","doi":"10.1016/j.fss.2025.109732","DOIUrl":"10.1016/j.fss.2025.109732","url":null,"abstract":"<div><div>This work studies the fixed-time event-triggered fault-tolerant containment control problem for nonlinear multi-agent system (MAS) with actuator faults. First, by leveraging fuzzy logic system to approximate unknown nonlinear dynamics, a state observer is designed to estimate unmeasurable state variables. Second, to handle the actuator fault, a novel projection operator compensation mechanism is developed. Furthermore, a fixed-time nonlinear filter design is given to solve the explosion problem and dynamic event-triggering mechanism is proposed to save system resources. Then, combined with dynamic surface control and fuzzy control techniques, fixed-time adaptive fault-tolerant containment control strategy is proposed with rigorous stability analysis, and all followers are able to converge to the convex hull constructed by leaders. In contrast with existing approaches, the main superiority of the proposed containment control strategy is that the projection operator can handle actuator faults more efficiently, multiple parameters of nonlinear filter enhance system flexibility and dynamic threshold in triggering conditions helps to reduce triggering frequency. Finally, simulation results confirm that the proposed method ensures fixed-time convergence of the containment errors.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"529 ","pages":"Article 109732"},"PeriodicalIF":2.7,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Innovative Razumikhin method for finite-time projective synchronization in fractional delay-coupled fuzzy memristive neural networks with jump mismatches 具有跳跃失配的分数阶延迟耦合模糊记忆神经网络有限时间投影同步的创新Razumikhin方法

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-04-15 Epub Date: 2025-12-20 DOI: 10.1016/j.fss.2025.109742

Wenqi Zhang , Xiang Wu , Hai Zhang , Xiaofeng Ye , Jinde Cao

引用次数: 0

RF-WFCCL: A random forest-driven weighted fuzzy concept cognitive learning 随机森林驱动的加权模糊概念认知学习

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-04-15 Epub Date: 2025-12-15 DOI: 10.1016/j.fss.2025.109724

Weihua Xu, Chongze Zhang

{"title":"RF-WFCCL: A random forest-driven weighted fuzzy concept cognitive learning","authors":"Weihua Xu, Chongze Zhang","doi":"10.1016/j.fss.2025.109724","DOIUrl":"10.1016/j.fss.2025.109724","url":null,"abstract":"<div><div>Weighted Fuzzy Concept Cognitive Learning (WFCCL) improves concept learning by assigning different weights to attributes. However, existing weighting methods mainly rely on fuzzy entropy and fail to effectively handle the noise, uncertainty, and complexity commonly present in real-world data. Moreover, the key threshold <em>λ</em> for generating Advanced Weighted Fuzzy Concepts (AWFC) has not been thoroughly investigated, which may limit the depth of knowledge discovery and the applicability of the model. To address these issues, this paper proposes a Random Forest-Driven Weighted Fuzzy Concept Cognitive Learning (RF-WFCCL) method. The proposed approach leverages random forests to compute attribute importance, thereby making weight allocation more reflective of data characteristics and reducing the influence of noise and uncertainty. In addition, an adaptive optimization algorithm is designed to automatically determine the approximately optimal threshold <span><math><mrow><mover><mi>λ</mi><mo>^</mo></mover><mrow><mo>(</mo><mi>i</mi><mo>)</mo></mrow></mrow></math></span> for generating AWFC, enhancing the accuracy and applicability of concept cognition. Unlike traditional methods, our model not only improves the adaptability of weight allocation but also introduces a data-driven threshold optimization strategy to facilitate knowledge discovery. Finally, extensive experiments on 12 datasets using 12 classification algorithms demonstrate the feasibility and superiority of the proposed method.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"529 ","pages":"Article 109724"},"PeriodicalIF":2.7,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145842543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Specificity measures based on fuzzy set inequality 基于模糊集不等式的特异性测度

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-04-15 Epub Date: 2025-12-19 DOI: 10.1016/j.fss.2025.109744

Nicolás Marín , Gustavo Rivas-Gervilla , Daniel Sánchez

引用次数: 0

Representation and construction of the classes Umin1 and Umax0 of uninorms on a bounded lattice 有界格上一致子的类Umin1和Umax0的表示和构造

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-04-15 Epub Date: 2025-11-15 DOI: 10.1016/j.fss.2025.109682

Hua-Peng Zhang , Yao Ouyang

引用次数: 0

A revised and extended version of McShane-Whitney extensions for fuzzy Lipschitz maps 模糊Lipschitz地图的McShane-Whitney扩展的修订和扩展版本

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-04-15 Epub Date: 2025-12-17 DOI: 10.1016/j.fss.2025.109731

Eduardo Jiménez-Fernández , Jesús Rodríguez-López , Aurora Sánchez-Martín-Orozco , Enrique A. Sánchez-Pérez

引用次数: 0

Neighbourhood models induced by the Euclidean distance and the Kullback-Leibler divergence 欧几里得距离和Kullback-Leibler散度诱导的邻域模型

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-04-15 Epub Date: 2025-12-22 DOI: 10.1016/j.fss.2025.109745

Ignacio Montes

{"title":"Neighbourhood models induced by the Euclidean distance and the Kullback-Leibler divergence","authors":"Ignacio Montes","doi":"10.1016/j.fss.2025.109745","DOIUrl":"10.1016/j.fss.2025.109745","url":null,"abstract":"<div><div>Robust statistics aims to develop methods that ensure the obtained results remain stable regardless of the quality of the data. A natural approach to enhancing the robustness of a probabilistic model is to consider a neighbourhood around a probability measure with a given radius. These models require two tools: a function for comparing probability measures and the radius measuring the level of imprecision or robustness to be added to the model. With these tools, a neighbourhood or distortion model is defined as the closed ball centred at the probability measure. Many well-known robust models, such as the ϵ-contamination, pari-mutuel model, or constant odds ratio, can be incorporated into the broader framework of neighbourhood models. Additionally, distances between probability measures, such as the total variation or the Kolmogorov distances, determine a neighbourhood model. This paper delves into the neighbourhood models induced by the Euclidean distance applied to the probability mass functions and the Kullback-Leibler divergence. For investigating these models from the perspective of imprecise probability theory, we make use of common optimisation tools with restrictions. We conclude this study providing a comparison study among different neighbourhood models.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"529 ","pages":"Article 109745"},"PeriodicalIF":2.7,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145885601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The uncertainty importance measure analysis for fuzzy structural systems based on possibilistic variance 基于可能性方差的模糊结构系统不确定性重要性测度分析

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-04-15 Epub Date: 2025-12-16 DOI: 10.1016/j.fss.2025.109743

Guijie Li , Yang Zhan , Huimin Xue

引用次数: 0

2-copulas and linear splines 2共轭和线性样条

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-04-15 Epub Date: 2025-12-20 DOI: 10.1016/j.fss.2025.109746

Fateme Kouchakinejad , Radko Mesiar , Andrea Stupňanová , Radomír Halaš

引用次数: 0

A transition-state-based zeroing neurodynamics method for solving non-fully/fully LR fuzzy Sylvester matrix equation 求解非全/全LR模糊Sylvester矩阵方程的过渡状态归零神经动力学方法

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-04-15 Epub Date: 2025-12-05 DOI: 10.1016/j.fss.2025.109715

Lei Jia , Weibao Xiong , Yiwei Li

{"title":"A transition-state-based zeroing neurodynamics method for solving non-fully/fully LR fuzzy Sylvester matrix equation","authors":"Lei Jia , Weibao Xiong , Yiwei Li","doi":"10.1016/j.fss.2025.109715","DOIUrl":"10.1016/j.fss.2025.109715","url":null,"abstract":"<div><div>Considering that traditional methods encounter theoretical infeasibility and computational complexity when solving fuzzy Sylvester matrix equations, by leveraging the advantages of zeroing neurodynamics approach for calculation problems, this paper proposes a transition-state-based zeroing neurodynamic (TSBZN) method to address non-fully/fully LR fuzzy Sylvester matrix equation (i.e., NLFSM and FLFSM equations). Based on the element-wise forms of the NLFSM and FLFSM equations which are mainly derived from LR fuzzy numbers and relative operations, two TSBZN models are constructed by defining the mass matrix. At the same time, a novel transition-state-based activation function (TSBAF) is designed and applied to enhance the performance of TSBZN models. In the TSBAF, a transition state parameter is introduced and divides the convergence process into two phases: a traveling phase and a reaching phase. The traveling phase ensures that the TSBZN models are continuously attracted to the transition state and rapidly converges to it, while the reaching phase guarantees stability and precise control. Consequently, the TSBZN models activated by the TSBAF possess superior fixed-time convergence with stricter upper bound on settling time, ensuring that the exact solutions of the NLFSM and FLFSM equations can be obtained within a fixed time. The global stability and fixed-time convergence of these two TSBZN models are theoretically proven, with predefined-time convergence further guaranteed by a corollary. Serial numerical experiments validate the accuracy, efficiency, and superiority of the TSBZN models, and an image denoising application also shows their practical value.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"529 ","pages":"Article 109715"},"PeriodicalIF":2.7,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145885600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0