Exponential and non-Exponential Based Generalized Similarity Measures for Complex Hesitant Fuzzy Sets with Applications. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Mahmood, Tahir; Rehman, Ubaid ur; Ali, Zeeshan
• Is Part Of: Fuzzy information and engineering. Volume 12:Issue 1(2020)
• Page Start: 38
• Page End: 70
• Publication Date: 2020-01-02
• Subjects: Complex fuzzy set -- complex hesitant fuzzy sets -- similarity measures; Fuzzy systems -- Periodicals; Intelligent control systems -- Periodicals; 629.89
• DOI: 10.1080/16168658.2020.1779013
• Languages: English
• ISSNs: 1616-8658

Abstract

Abstract : The purpose of this manuscript is to explore the notion of a complex hesitant fuzzy set (CHFS), as a generalization of the hesitant fuzzy set (HFS) and complex fuzzy set (CFS) to cope with the uncertain and complicated information in the real-world decision. CHFS contains truth grades in the form of a subset of the unit disc in the complex plane. The operational laws of the explored notion are also described. Further, the exponential based generalized similarity measures, without exponential based generalized similarity measures, and their important characteristics are also explored. These similarity measures are applied in the environment of pattern recognition and medical diagnosis to evaluate the proficiency and feasibility of the established measures. We also solved some numerical examples using the established measures. To examine the reliability and validity of the proposed measures by comparing it with existing measures. The advantages, comparative analysis, and graphical representation of the explored measures and existing measures are also discussed in detail.