An axiomatically supported divergence measures for q‐rung orthopair fuzzy sets. Issue 10 (21st July 2021)

• Record Type: Journal Article
• Authors: Khan, Muhammad Jabir; Alcantud, José Carlos R.; Kumam, Poom; Kumam, Wiyada; Al‐Kenani, Ahmad N.
• Is Part Of: International journal of intelligent systems. Volume 36:Issue 10(2021)
• Page Start: 6133
• Page End: 6155
• Publication Date: 2021-07-21
• Subjects: divergence measures -- entropy -- MABAC method -- qROFS; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.22545
• Languages: English
• ISSNs: 0884-8173

Abstract

Abstract: Despite the importance of divergence measures, the literature has not provided a satisfactory formulation for the case of q‐rung orthopair fuzzy set. This paper criticizes the existing attempts in terms of respect of the basic axioms of a divergence measure. Then new improved, axiomatically supported divergence measures for qROFSs are proposed. Additional properties of the new divergence measures are discussed to guarantee their good performance. The transformation relationships with entropy and dissimilarity measures are debated. The multiattribute border approximation area comparison decision method is extended based on the suggested divergence measures, and it is applied to the selection of all‐rounder cricketer for a team.