Fuzzy Sets and Systems最新文献_第3页

On the coincidence of the Choquet integral and the pan-integral: An abstract setting and examples 关于Choquet积分与泛积分的重合：一个抽象的背景和例子

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-06-01 Epub Date: 2026-01-14 DOI: 10.1016/j.fss.2026.109774

M. Svistula, T. Sribnaya, R. Uzbekov

引用次数: 0

Estimation of a simple linear regression model for random star-shaped sets 随机星形集的简单线性回归模型估计

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-06-01 Epub Date: 2026-01-28 DOI: 10.1016/j.fss.2026.109800

J. Graña-Colubi , G. González-Rodríguez , A.B. Ramos-Guajardo

引用次数: 0

pseudo-FNN: Advancing fuzzy neural networks with pseudo-Unineurons and kernel density-based weights 伪神经网络（pseudo-FNN）：基于核密度权值的伪神经网络

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-06-01 Epub Date: 2026-01-22 DOI: 10.1016/j.fss.2026.109794

Paulo Vitor de Campos Souza

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引用次数: 0

Adaptive directional importance sampling with von Mises-Fisher mixture model for fuzzy reliability analysis 基于von Mises-Fisher混合模型的自适应方向重要性抽样模糊可靠性分析

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-06-01 Epub Date: 2026-01-24 DOI: 10.1016/j.fss.2026.109798

Xia Jiang, Kaichao Zhang, Xuan Zhao

{"title":"Adaptive directional importance sampling with von Mises-Fisher mixture model for fuzzy reliability analysis","authors":"Xia Jiang, Kaichao Zhang, Xuan Zhao","doi":"10.1016/j.fss.2026.109798","DOIUrl":"10.1016/j.fss.2026.109798","url":null,"abstract":"<div><div>To improve the computational efficiency of failure possibility estimation in fuzzy reliability analysis, this paper proposes an <strong>A</strong>daptive <strong>D</strong>irectional <strong>I</strong>mportance <strong>S</strong>ampling method (ADIS), which employs a von Mises–Fisher mixture (vMFM) model as the sampling density of direction vectors. The initial vMFM parameters are determined through uniform pre-sampling and clustering of failure samples by using the density-based spatial clustering of applications with noise clustering (DBSCAN) algorithm, while an intermediate event is introduced to address the scarcity of failure samples. During the adaptive iterative process, direction vectors are continuously drawn from the updated vMFM model, and their intersection points with the limit-state surface are obtained using an iterative root-finding strategy. Based on these intersection points, the vMFM parameters are iteratively refined through DBSCAN clustering and the expectation-maximization (EM) algorithm. Iteration continues until the updated vMFM model generates a sufficient number of direction vectors pointing to the true failure domain, yielding a quasi-optimal sampling density. Finally, the failure possibility is efficiently estimated by all accumulated intersection points throughout the iterative process. Example analyses demonstrate that the proposed method achieves superior efficiency compared with traditional directional simulation and existing simulation strategies.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"532 ","pages":"Article 109798"},"PeriodicalIF":2.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081317","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

A topological approach to fuzzy iterated function systems 模糊迭代函数系统的拓扑方法

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-06-01 Epub Date: 2026-01-20 DOI: 10.1016/j.fss.2026.109791

Taras Banakh , Krzysztof Caban , Filip Strobin

引用次数: 0

Geometric foundations of possibilistic clustering: A hard possibilistic clustering algorithm 可能性聚类的几何基础：一种硬可能性聚类算法

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-06-01 Epub Date: 2026-01-13 DOI: 10.1016/j.fss.2026.109775

James C. Bezdek, Thomas A. Runkler

引用次数: 0

Regular orders for triangular fuzzy numbers and the weak law of trichotomy 三角模糊数的正则阶数及弱三分律

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-06-01 Epub Date: 2026-01-22 DOI: 10.1016/j.fss.2026.109790

Jaime Cesar dos Santos

引用次数: 0

Matrix -driven feature selection for interval-valued data based on double fuzzy adaptive neighborhood consistency measure 基于双模糊自适应邻域一致性度量的矩阵驱动区间值数据特征选择

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-06-01 Epub Date: 2026-01-23 DOI: 10.1016/j.fss.2026.109795

Lu Wang , Yaya Liu , Keyun Qin , Zheng Pei

{"title":"Matrix -driven feature selection for interval-valued data based on double fuzzy adaptive neighborhood consistency measure","authors":"Lu Wang , Yaya Liu , Keyun Qin , Zheng Pei","doi":"10.1016/j.fss.2026.109795","DOIUrl":"10.1016/j.fss.2026.109795","url":null,"abstract":"<div><div>In granular computing, extracting effective features from imbalanced high-dimensional data remains a frontier challenge. Existing models for interval-valued fuzzy decision information systems (IFDS) have two critical limitations: fixed neighborhood radii fail to adapt to the local distribution characteristics of different features, and boundary information in granular structures is underutilized, leading to incomplete feature importance evaluation. For these limitations, we present a feature selection method for IFDS based on the double fuzzy adaptive neighborhood consistency measure. First, we define a novel fuzzy adaptive neighborhood radius to dynamically optimize the neighborhood structure, establish a fuzzy adaptive neighborhood rough set model for IFDS with rigorous axiomatic analysis, and further construct the double fuzzy adaptive neighborhood consistency measure to comprehensively capture deterministic and uncertain relationships between features and fuzzy decisions. Additionally, a matrix-based feature selection algorithm is designed to enhance computational efficiency for high-dimensional data. Through comparative experiments conducted on nine datasets, the experimental results demonstrate that the proposed model and algorithm achieve significant advantages in approximation accuracy and classification performance.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"532 ","pages":"Article 109795"},"PeriodicalIF":2.7,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146049217","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

Ω-vector spaces Ω向量空间

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-05-15 Epub Date: 2026-01-16 DOI: 10.1016/j.fss.2026.109776

Patricia Ferrero , Jorge Jiménez , María Luisa Serrano , Branimir Šešelja , Andreja Tepavčević

引用次数: 0

Characterizations and relation of generalized differentiabilities of interval-valued functions and fuzzy number-valued functions 区间值函数和模糊值函数的广义可微性的刻画及其关系

IF 2.7 1区数学

Fuzzy Sets and Systems Pub Date : 2026-05-15 Epub Date: 2026-01-20 DOI: 10.1016/j.fss.2026.109789

Dong Qiu , Nianxi Huang , Yandan Jiang

引用次数: 0