Orthopairian fuzzy similarity based on below, above and centre fuzzy sets with applications to pattern recognition and identification of best ISP

Similarity measure plays an important role when estimating the degree of resemblance between two sets or objects. A variety of similarity measures are suggested in the literature in the context of fuzzy sets and their generalizations, but a similarity measure of q-rung orthopair fuzzy sets (q-ROFS...

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Main Authors: Zahid Hussain, Yasmeen Bano, Sahar Abbas, Rashid Hussain, Muhammad Alam
Format: Article
Language:English
Published: Prince of Songkla University 2024-10-01
Series:Songklanakarin Journal of Science and Technology (SJST)
Subjects:
Online Access:https://sjst.psu.ac.th/journal/46-5/6.pdf
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author Zahid Hussain
Yasmeen Bano
Sahar Abbas
Rashid Hussain
Muhammad Alam
author_facet Zahid Hussain
Yasmeen Bano
Sahar Abbas
Rashid Hussain
Muhammad Alam
author_sort Zahid Hussain
collection DOAJ
description Similarity measure plays an important role when estimating the degree of resemblance between two sets or objects. A variety of similarity measures are suggested in the literature in the context of fuzzy sets and their generalizations, but a similarity measure of q-rung orthopair fuzzy sets (q-ROFSs) based on below, above and centre fuzzy sets has not been considered so far. Therefore, in this paper, we propose a novel similarity measure based on the information carried by transforming q-rung orthopair fuzzy sets into their below, above and centre fuzzy sets to calculate the degree of similarity between two q-ROFSs. We also construct an axiomatic definition for the proposed similarity measure of q-ROFS. Furthermore, to show the competency, reliability and applicability of our proposed similarity measure, we present several examples related to pattern recognition and multicriteria decision making. Finally, we construct an algorithm for Orthopairian Portuguese interactive and multicriteria decision making (O-TODIM) based on our proposed similarity measure between q-ROFSs, to handle complex multicriteria decision making problems related to daily life. Our demonstration shows that the proposed method is reasonable and reliable in handling different problems related to daily life settings in the q-ROFSs environment.
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issn 0125-3395
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publishDate 2024-10-01
publisher Prince of Songkla University
record_format Article
series Songklanakarin Journal of Science and Technology (SJST)
spelling doaj-art-e4359c5ee8e54602a1b0d1b95a3ee1082025-08-20T01:58:37ZengPrince of Songkla UniversitySongklanakarin Journal of Science and Technology (SJST)0125-33952024-10-01465438449Orthopairian fuzzy similarity based on below, above and centre fuzzy sets with applications to pattern recognition and identification of best ISPZahid Hussain0Yasmeen Bano1Sahar Abbas2Rashid Hussain3Muhammad Alam4Department of Mathematical Science, Karakoram International University, Gilgit-Baltistan, 15100 PakistanDepartment of Mathematical Science, Karakoram International University, Gilgit-Baltistan, 15100 PakistanDepartment of Mathematical Science, Karakoram International University, Gilgit-Baltistan, 15100 PakistanDepartment of Mathematical Science, Karakoram International University, Gilgit-Baltistan, 15100 PakistanDepartment of Earth Science, Karakoram International University, Gilgit-Baltistan, 15100 PakistanSimilarity measure plays an important role when estimating the degree of resemblance between two sets or objects. A variety of similarity measures are suggested in the literature in the context of fuzzy sets and their generalizations, but a similarity measure of q-rung orthopair fuzzy sets (q-ROFSs) based on below, above and centre fuzzy sets has not been considered so far. Therefore, in this paper, we propose a novel similarity measure based on the information carried by transforming q-rung orthopair fuzzy sets into their below, above and centre fuzzy sets to calculate the degree of similarity between two q-ROFSs. We also construct an axiomatic definition for the proposed similarity measure of q-ROFS. Furthermore, to show the competency, reliability and applicability of our proposed similarity measure, we present several examples related to pattern recognition and multicriteria decision making. Finally, we construct an algorithm for Orthopairian Portuguese interactive and multicriteria decision making (O-TODIM) based on our proposed similarity measure between q-ROFSs, to handle complex multicriteria decision making problems related to daily life. Our demonstration shows that the proposed method is reasonable and reliable in handling different problems related to daily life settings in the q-ROFSs environment.https://sjst.psu.ac.th/journal/46-5/6.pdffuzzy setq-rung orthopair fuzzy setssimilarity measurespattern recognitiono-todimmulticriteria decision making
spellingShingle Zahid Hussain
Yasmeen Bano
Sahar Abbas
Rashid Hussain
Muhammad Alam
Orthopairian fuzzy similarity based on below, above and centre fuzzy sets with applications to pattern recognition and identification of best ISP
Songklanakarin Journal of Science and Technology (SJST)
fuzzy set
q-rung orthopair fuzzy sets
similarity measures
pattern recognition
o-todim
multicriteria decision making
title Orthopairian fuzzy similarity based on below, above and centre fuzzy sets with applications to pattern recognition and identification of best ISP
title_full Orthopairian fuzzy similarity based on below, above and centre fuzzy sets with applications to pattern recognition and identification of best ISP
title_fullStr Orthopairian fuzzy similarity based on below, above and centre fuzzy sets with applications to pattern recognition and identification of best ISP
title_full_unstemmed Orthopairian fuzzy similarity based on below, above and centre fuzzy sets with applications to pattern recognition and identification of best ISP
title_short Orthopairian fuzzy similarity based on below, above and centre fuzzy sets with applications to pattern recognition and identification of best ISP
title_sort orthopairian fuzzy similarity based on below above and centre fuzzy sets with applications to pattern recognition and identification of best isp
topic fuzzy set
q-rung orthopair fuzzy sets
similarity measures
pattern recognition
o-todim
multicriteria decision making
url https://sjst.psu.ac.th/journal/46-5/6.pdf
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