NDLI: Information Measures Based on T-Spherical Fuzzy Sets and Their Applications in Decision Making and Pattern Recognition

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Information Measures Based on T-Spherical Fuzzy Sets and Their Applications in Decision Making and Pattern Recognition

Content Provider	MDPI
Author	Shen, Xiaomin Sakhi, Sidra Ullah, Kifayat Abid, Muhammad Nabeel Jin, Yun
Copyright Year	2022
Description	The T-spherical fuzzy set (TSFS) is a modification of the fuzzy set (FS), intuitionistic fuzzy set (IFS), Pythagorean fuzzy set (PyFS), q-rung orthopair fuzzy set (q-ROFS), and picture fuzzy set (PFS), with three characteristic functions: the membership degree (MD) denoted by $S$ , the nonmembership degree (NMD) denoted by $D$ , and the abstinence degree (AD) denoted by $I$ . It can be used to solve problems of uncertain information with no restrictions. The distance measure (DM) is a tool that sums up the difference between points, while the similarity measure (SM) is a method applied to calculate the similarity between objects within an interval of $[0,1]$ . The current work aims to introduce novel DMs and SMs in the environment of TSFSs to show the limitations of the previously defined DMs and SMs. The suggested DMs and SMs provide more room for all three degrees to be selected without restriction. We investigated the effectiveness of the proposed DMs and SMs by applying a pattern-recognition technique, and we determined their applicability for multicriteria decision making (MCDM) using numerical examples. The newly proposed DMs and SMs are briefly compared to existing DMs and SMs, and appropriate conclusions are drawn.
Starting Page	302
e-ISSN	20751680
DOI	10.3390/axioms11070302
Journal	Axioms
Issue Number	7
Volume Number	11
Language	English
Publisher	MDPI
Publisher Date	2022-06-21
Access Restriction	Open
Subject Keyword	Axioms Artificial Intelligence T-spherical Fuzzy Set (tsfs) Distance Measure (dm) Similarity Measure (sm) Pattern Recognition Multicriteria Decision Making (mcdm)
Content Type	Text
Resource Type	Article

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