Information measures for MADM under m-polar neutrosophic environment

Abstract

Multiploar information plays a vital role in making reliable decisions in one's daily life encompassing micro to large scale decisions. These decision making problems often include imprecise and inconsistent data. This article presents some information measures including similarity, distance, correlation, divergence and Dice measures for m-polar neutrosophic sets. Desirable characteristics of these measures are also presented. The notions of angle of similarity between two m-polar neutrosophic sets, λ-similarity, entropy and less and more fuzzy are also made part of the discussion. An application of m-polar neutrosophic sets using the suggested measures in health sciences accompanied by five algorithms is also presented. Finally, comparative analysis of the proposed information measures with some existing measures is also presented.