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

CAAI Transactions on Intelligence Technology

article

Zeeshan Ali¹  Tahir Mahmood¹ 

[1] Department of Mathematics and Statistics, International Islamic University

关键词: pattern recognition;    fuzzy set theory;    decision making;    complex neutrosophic generalised dice similarity measures;    decision making;    complex neutrosophic set;    CNS;    complex fuzzy set;    complicated information;    inconsistent information;    fuzzy set theory;    complex-valued membership;    complex-valued abstinence;    complex-valued nonmembership;    weighted generalised dice similarity measures;    pattern recognition model;    C1160 Combinatorial mathematics;    C1290 Applications of systems theory;   

DOI  :  10.1049/trit.2019.0084

学科分类：数学（综合）

来源: Wiley

【 摘 要 】

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.

【 授权许可】

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