Similarity Measures and Multi-person TOPSIS Method Using m-polar Single-Valued Neutrosophic Sets

Abstract

In this paper, we give a new notion of the m-polar single-valued neutrosophic sets (m-PSVNSs) which is a hybrid of the single-valued neutrosophic sets (SVNSs) and the m-polar fuzzy sets (m-PFSs) and study several of the structure operations including subset, equal, union, intersection, and complement. Subsequently, we present the basic definitions, theorems, and examples on m-PSVNSs. Also, we define the certain distance between two m-PSVNSs and a novel similarity measure for m-PSVNSs based on distances. A multi criteria decision-making (MCDM) problem is animated for m-PSVNS data that takes into account the distances for the best alternative (solution) by an application of similarity measure for m-PSVNSs in brand recognition. Finally, we construct a new methodology to extend the TOPSIS to m-PSVNS and illustrate its applicability via a numerical example.

Keywords

• m-polar single-valued neutrosophic set
• Distance measure
• Ssimilarity measure
• Pattern recognition
• Multi-person TOPSIS technique