A new picture fuzzy divergence measure based on Jensen-Tsallis information measure and its application to multicriteria decision making

Ratika Kadian; Satish Kumar

doi:10.1007/s41066-021-00254-6

A new picture fuzzy divergence measure based on Jensen-Tsallis information measure and its application to multicriteria decision making

Granul Comput. 2022;7(1):113-126. doi: 10.1007/s41066-021-00254-6. Epub 2021 Mar 14.

Authors

Ratika Kadian¹, Satish Kumar¹

Affiliation

¹ Department of Mathematics, Maharishi Markandeshwar (Deemed To Be University), Mullana, Ambala, 133207 India.

Abstract

Picture Fuzzy Sets (PFSs) originated by Cuong and Kreinovich are more capable to capture uncertain, inconsistent and vague information in multi-criteria decision making. In this paper, we propose a new picture fuzzy divergence measure based on Jensen-Tsallis function between PFSs. Further, the concept has been extended from fuzzy sets to novel picture fuzzy divergence measure. Besides the validation of the proposed measure, some of its key properties with specific cases are additionally talked about. The performance of the proposed measure is compared with other existing measures in the literature. Some illustrative examples are provided in the context of novel rapacious COVID-19 and pattern recognition which demonstrate the adequacy and practicality of the proposed approach in solving real-life problems.

Keywords: COVID-19; Coronavirus disease; Jensen inequality; MCDM; Picture fuzzy set.