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New Distance Measure of Single‐Valued Neutrosophic Sets and Its Application
Author(s) -
Huang HanLiang
Publication year - 2016
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21815
Subject(s) - measure (data warehouse) , similarity measure , falsity , indeterminacy (philosophy) , mathematics , membership function , entropy (arrow of time) , score , fuzzy set , similarity (geometry) , set (abstract data type) , data mining , set function , cluster analysis , computer science , artificial intelligence , fuzzy logic , statistics , linguistics , philosophy , physics , quantum mechanics , image (mathematics) , programming language
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.