Extending intuitionistic operations, orderings, and entropy measures on generalized fuzzy orthopartitions

IF 3.2 1区数学 Q2 COMPUTER SCIENCE, THEORY & METHODS

Fuzzy Sets and Systems Pub Date : 2025-03-26 DOI:10.1016/j.fss.2025.109381

Stefania Boffa , Davide Ciucci , Christophe Marsala

引用次数: 0

Abstract

Generalized fuzzy orthopartitions extend the traditional concept of partitions to include both fuzziness and uncertainty. A generalized fuzzy orthopartition is a collection of intuitionistic fuzzy sets representing equivalence classes and satisfying a specific pair of axioms, which capture the idea that the classes must be disjoint and cover the initial universe. The aim of this article is twofold. Firstly, we aggregate and order generalized fuzzy orthopartitions by extending intuitionistic operations and relations. Secondly, we introduce and study entropy measures on generalized fuzzy orthopartitions by employing entropies on intuitionistic fuzzy sets already existing in the literature.

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

Fuzzy Sets and Systems 数学-计算机：理论方法

CiteScore

6.50

自引率

17.90%

发文量

321

审稿时长

6.1 months

期刊介绍： Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.