Evaluating performance of novel similarity measures of Pythagorean fuzzy sets and their applications in pattern recognition and medical diagnosis

Hari Darshan Arora and Anjali Naithani ()
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Hari Darshan Arora: Amity Institute of Applied Sciences, Amity University
Anjali Naithani: Amity Institute of Applied Sciences, Amity University

International Journal of System Assurance Engineering and Management, 2024, vol. 15, issue 7, No 46, 3485-3494

Abstract: Abstract Yager (2013 joint IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS), 10.1109/ifsa-nafips.2013.6608375, 2013) first proposed the notion of Pythagorean fuzzy sets (PFS), which provides a unique procedure to characterize vagueness and uncertainty with greater accuracy and precision than intuitionistic fuzzy sets (IFS). The notion was established mathematically to explain vagueness and ambiguity and to deliver a structured instrument for dealing with vagueness in real-world situations. In this paper, performance of similarity measures of PFS based on the secant function, considering participation grade, non- participation grade, and hesitancy have been established. Axioms related to similarity measures have also been proved for the proposed measures. These similarity measurements, as well as weighted similarity measures between PFS have then been used for the performance of recognition of patterns and medical analysis. Two case studies have been provided to highlight the utility of similarity measures. Finally, to determine the efficacy of the recommended measures, a comparative study is also conducted.

Keywords: Intuitionistic fuzzy set; Pythagorean fuzzy sets; Similarity measure; Medical diagnosis and pattern recognition; 03E72; 94D05; 03B52 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13198-024-02355-2

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