Spherical Fuzzy Credibility Dombi Aggregation Operators and Their Application in Artificial Intelligence

It was recently proposed to extend the spherical fuzzy set to spherical fuzzy credibility sets (SFCSs). In this paper, we define the concept of SFCSs. We then define new operational laws for SFCSs using Dombi operational laws. Various spherical fuzzy credibility aggregation operators such as spheric...

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Main Authors: Neelam Khan, Muhammad Qiyas, Darjan Karabasevic, Muhammad Ramzan, Mubashir Ali, Igor Dugonjic, Dragisa Stanujkic
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Axioms
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Online Access:https://www.mdpi.com/2075-1680/14/2/108
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author Neelam Khan
Muhammad Qiyas
Darjan Karabasevic
Muhammad Ramzan
Mubashir Ali
Igor Dugonjic
Dragisa Stanujkic
author_facet Neelam Khan
Muhammad Qiyas
Darjan Karabasevic
Muhammad Ramzan
Mubashir Ali
Igor Dugonjic
Dragisa Stanujkic
author_sort Neelam Khan
collection DOAJ
description It was recently proposed to extend the spherical fuzzy set to spherical fuzzy credibility sets (SFCSs). In this paper, we define the concept of SFCSs. We then define new operational laws for SFCSs using Dombi operational laws. Various spherical fuzzy credibility aggregation operators such as spherical fuzzy credibility Dombi weighted averaging (SFCDWA), spherical fuzzy credibility Dombi ordered weighted averaging (SFCDOWA), spherical fuzzy credibility Dombi weighted geometric (SFCDWG), and spherical fuzzy credibility Dombi ordered weighted geometric (SFCDOWG) are defined. We also show the boundedness, monotonicity, and idempotency aspects of the suggested operators. We proposed the spherical fuzzy credibility entropy to find the unknown weight information of the attributes. Symmetry analysis is a useful and important tool in artificial intelligence that may be used in a variety of fields. To calculate the significant factor, we determine the multi-attribute decision-making (MADM) method using the suggested operators for SFCSs to increase the value of the assessed operators. To demonstrate the effectiveness and superiority of the suggested approach, we compare our findings to those of many other approaches.
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spelling doaj-art-222c004f3cb24f419fa808c4b5404c2a2025-08-20T03:11:58ZengMDPI AGAxioms2075-16802025-01-0114210810.3390/axioms14020108Spherical Fuzzy Credibility Dombi Aggregation Operators and Their Application in Artificial IntelligenceNeelam Khan0Muhammad Qiyas1Darjan Karabasevic2Muhammad Ramzan3Mubashir Ali4Igor Dugonjic5Dragisa Stanujkic6Department of Mathematics, Abdul Wali Khan University Mardan, Mardan 23200, PakistanDepartment of Mathematics, Riphah International University Faisalabad Campus, Faisalabad 38000, PakistanDepartment of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai 602105, Tamil Nadu, IndiaDepartment of Mathematics, Riphah International University Faisalabad Campus, Faisalabad 38000, PakistanDepartment of Mathematics, Riphah International University Faisalabad Campus, Faisalabad 38000, PakistanFaculty of Information Technologies, Pan-European University "APEIRON", Vojvode Pere Krece 13, 78102 Banja Luka, Bosnia and HerzegovinaTechnical Faculty in Bor, University of Belgrade, Vojske Jugoslavije 12, 19210 Bor, SerbiaIt was recently proposed to extend the spherical fuzzy set to spherical fuzzy credibility sets (SFCSs). In this paper, we define the concept of SFCSs. We then define new operational laws for SFCSs using Dombi operational laws. Various spherical fuzzy credibility aggregation operators such as spherical fuzzy credibility Dombi weighted averaging (SFCDWA), spherical fuzzy credibility Dombi ordered weighted averaging (SFCDOWA), spherical fuzzy credibility Dombi weighted geometric (SFCDWG), and spherical fuzzy credibility Dombi ordered weighted geometric (SFCDOWG) are defined. We also show the boundedness, monotonicity, and idempotency aspects of the suggested operators. We proposed the spherical fuzzy credibility entropy to find the unknown weight information of the attributes. Symmetry analysis is a useful and important tool in artificial intelligence that may be used in a variety of fields. To calculate the significant factor, we determine the multi-attribute decision-making (MADM) method using the suggested operators for SFCSs to increase the value of the assessed operators. To demonstrate the effectiveness and superiority of the suggested approach, we compare our findings to those of many other approaches.https://www.mdpi.com/2075-1680/14/2/108spherical fuzzy credibility setsdombi operationspherical fuzzy credibility set aggregation operatorsdecision making
spellingShingle Neelam Khan
Muhammad Qiyas
Darjan Karabasevic
Muhammad Ramzan
Mubashir Ali
Igor Dugonjic
Dragisa Stanujkic
Spherical Fuzzy Credibility Dombi Aggregation Operators and Their Application in Artificial Intelligence
Axioms
spherical fuzzy credibility sets
dombi operation
spherical fuzzy credibility set aggregation operators
decision making
title Spherical Fuzzy Credibility Dombi Aggregation Operators and Their Application in Artificial Intelligence
title_full Spherical Fuzzy Credibility Dombi Aggregation Operators and Their Application in Artificial Intelligence
title_fullStr Spherical Fuzzy Credibility Dombi Aggregation Operators and Their Application in Artificial Intelligence
title_full_unstemmed Spherical Fuzzy Credibility Dombi Aggregation Operators and Their Application in Artificial Intelligence
title_short Spherical Fuzzy Credibility Dombi Aggregation Operators and Their Application in Artificial Intelligence
title_sort spherical fuzzy credibility dombi aggregation operators and their application in artificial intelligence
topic spherical fuzzy credibility sets
dombi operation
spherical fuzzy credibility set aggregation operators
decision making
url https://www.mdpi.com/2075-1680/14/2/108
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AT muhammadramzan sphericalfuzzycredibilitydombiaggregationoperatorsandtheirapplicationinartificialintelligence
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