On Similarity Measures Between Pythagorean Fuzzy Sets Derived from Overlap and Grouping Functions

Jia, Zihang; Qiao, Junsheng; Chen, Minghao

doi:10.1007/s40815-023-01515-z

Cited by 3 publications

(1 citation statement)

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“…Overlap functions measure the degree of certainty to which an object belongs simultaneously to two classes while grouping functions quantify the degree to which the same object belongs to any of the considered classes. These functions have found applications in tasks involving a maximal lack of information and fuzzy preference modeling and have been extensively studied in multi-attribute decision-making [7], rule-based classification [8], and image processing [9].…”

Section: Introductionmentioning

confidence: 99%

Some Construction Methods for Pseudo-Overlaps and Pseudo-Groupings and Their Application in Group Decision Making

García-Zamora

Paiva

Cruz

et al. 2023

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In many real-world scenarios, the importance of different factors may vary, making commutativity an unreasonable assumption for aggregation functions, such as overlaps or groupings. To address this issue, researchers have introduced pseudo-overlaps and pseudo-groupings as their corresponding non-commutative generalizations. In this paper, we explore various construction methods for obtaining pseudo-overlaps and pseudo-groupings using overlaps, groupings, fuzzy negations, convex sums, and Riemannian integration. We then show the applicability of these construction methods in a multi-criteria group decision-making problem, where the importance of both the considered criteria and the experts vary. Our results highlight the usefulness of pseudo-overlaps and pseudo-groupings as a non-commutative alternative to overlaps and groupings.

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Section: Introductionmentioning

confidence: 99%