Paper Info
Title
Complex Neutrosophic Generalized 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 complicated and inconsistent information in the environment of fuzzy set theory. The CNS is characterised by three functions expressing the degree of complex-valued membership, complex-valued abstinence and degree of complex-valued non-membership. The aim of this manuscript is to initiate the novel dice similarity measures and generalised dice similarity 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 the generalised dice similarity measures and weighted generalised dice similarity measures using CNS to the pattern recognition model to examine the reliability and superiority of the established approaches. The advantages and 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.
Year
DOI
Venue
2020
10.1049/trit.2019.0084
CAAI Transactions on Intelligence Technology
Keywords
DocType
Volume
pattern recognition,fuzzy set theory,decision making
Journal
5
Issue
ISSN
Citations 
2
2468-6557
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Zeeshan Ali100.34
Tahir Mahmood29528.76