New Distance Measure of Single-Valued Neutrosophic Sets and Its Application

Abstract

A single-valued neutrosophic set (SVNS) is an instance of a neutrosophic set, which can be used to handle uncertainty, imprecise, indeterminate, and inconsistent information in real life. In this paper, a new distance measure between two SVNSs is defined by the full consideration of truth-membership function, indeterminacy-membership function, and falsity-membership function for the forward and backward differences. Then the similarity measure, the entropy measure, and the index of distance are also presented. Finally, two illustrative examples are given to demonstrate the effectiveness of the proposed clustering method and multicriteria decision-making method based on the distance (similarity) measure between SVNSs.