A dissimilarity Jensen–Shannon divergence measure for intuitionistic fuzzy sets. Issue 11 (25th July 2018)

• Record Type: Journal Article
• Authors: Joshi, Rajesh; Kumar, Satish
• Is Part Of: International journal of intelligent systems. Volume 33:Issue 11(2018)
• Page Start: 2216
• Page End: 2235
• Publication Date: 2018-07-25
• Subjects: divergence measure -- intuitionistic fuzzy dissimilarity measure -- intuitionistic fuzzy set -- multiple attribute decision making -- pattern recognition; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.22026
• Languages: English
• ISSNs: 0884-8173

Abstract

Abstract: The need of suitable divergence measures arise as they play an important role in discrimination of two probability distributions. The present communication is devoted to the introduction of one such divergence measure using Jensen inequality and Shannon entropy and its validation. Also, a new dissimilarity measure based on the proposed divergence measure is introduced. Besides establishing validation, some of its major properties are also studied. Further, a new multiple attribute decision making method based on a proposed dissimilarity measure is introduced and is thoroughly explained with the help of an illustrated example. The paper is summed up with an application of the proposed dissimilarity measure in pattern recognition.