Complex neutrosophic generalised dice similarity measures and their application to decision making

Abstract

Complex neutrosophic set (CNS) is a modified version of the complex fuzzy set, to cope with complicatedand inconsistent information in the environment of fuzzy set theory. The CNS is characterised by three functionsexpressing the degree of complex-valued membership, complex-valued abstinence and degree of complex-valuednon-membership. The aim of this manuscript is to initiate the novel dice similarity measures and generalised dicesimilarity using CNS. The special cases of the investigated measures are discussed with the help of some remarks.Moreover, some distance measures based on CNS are also proposed in this manuscript. Then, the authors applied thegeneralised dice similarity measures and weighted generalised dice similarity measures using CNS to the patternrecognition model to examine the reliability and superiority of the established approaches. The advantagesand comparative analysis of the proposed measures with existing measures are also discussed in detail. At last,a numerical example is provided to illustrate the validity and applicability of the presented measures.