{"title":"General ordinal sums of (pseudo-quasi) overlap and grouping functions","authors":"Ting-hai Zhang , Feng Qin , Jie Wan , Wenhuang Li","doi":"10.1016/j.fss.2026.109824","DOIUrl":null,"url":null,"abstract":"<div><div>In this work, we extend the existing ordinal sum constructions of fuzzy negations and fuzzy Sheffer strokes, which are based on the standard negation, to general ordinal sum structures derived from arbitrary negations. We also establish equivalent characterizations of their fundamental properties. Building upon this foundation and leveraging the completeness of the fuzzy Sheffer stroke, which provides a robust theoretical basis for designing fuzzy logic operators, we construct general ordinal sum structures for overlap (grouping) functions and pseudo-quasi overlap (grouping) functions. In these novel constructions, the range of function values within each summand interval is extended from the summand interval itself to an interval determined jointly by the summand interval and an arbitrary automorphism or quasi automorphism. Similarly, the function values outside the summand intervals are generalized from the identity mapping to an automorphism or quasi automorphism on [0,1]. This approach not only generalizes the existing corresponding ordinal sum structures but also substantially broadens their scope, thereby offering new perspectives for developing richer and more flexible ordinal sum constructions for other fuzzy logic operators.</div></div>","PeriodicalId":55130,"journal":{"name":"Fuzzy Sets and Systems","volume":"533 ","pages":"Article 109824"},"PeriodicalIF":2.7000,"publicationDate":"2026-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fuzzy Sets and Systems","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165011426000631","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/2/19 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
In this work, we extend the existing ordinal sum constructions of fuzzy negations and fuzzy Sheffer strokes, which are based on the standard negation, to general ordinal sum structures derived from arbitrary negations. We also establish equivalent characterizations of their fundamental properties. Building upon this foundation and leveraging the completeness of the fuzzy Sheffer stroke, which provides a robust theoretical basis for designing fuzzy logic operators, we construct general ordinal sum structures for overlap (grouping) functions and pseudo-quasi overlap (grouping) functions. In these novel constructions, the range of function values within each summand interval is extended from the summand interval itself to an interval determined jointly by the summand interval and an arbitrary automorphism or quasi automorphism. Similarly, the function values outside the summand intervals are generalized from the identity mapping to an automorphism or quasi automorphism on [0,1]. This approach not only generalizes the existing corresponding ordinal sum structures but also substantially broadens their scope, thereby offering new perspectives for developing richer and more flexible ordinal sum constructions for other fuzzy logic operators.
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.