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 information measures for m-polar neutrosophic sets. These include similarity, distance, correlation, divergence and Dice measures for m-polar neutrosophic sets. Furthermore, the paper presents the desirable characteristics of these measures along with the notions of angle of similarity between two m-polar neutrosophic sets, \(\lambda\)-similarity, entropy and less and more fuzzy aspects. The paper also presents an application of m-polar neutrosophic sets using the suggested measures in health sciences accompanied by five algorithms. Moreover, the paper presents the comparative analysis of the proposed information measures with some existing measures.