Advancing AI-Based Biometric Authentication in Multi-Criteria Decision Approach Using Complex Circular Intuitionistic Fuzzy Logic and Dombi Operators

Advancing AI-Based Biometric Authentication in Multi-Criteria Decision Approach Using Complex Circular Intuitionistic Fuzzy Logic and Dombi Operators | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Advancing AI-Based Biometric Authentication in Multi-Criteria Decision Approach Using Complex Circular Intuitionistic Fuzzy Logic and Dombi Operators Munazza Amin, Kifayat Ullah, Maria Akram, Raiha Imran, Muhammad Safdar Nazeer This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4483111/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In the realm of biometric authentication systems, the challenge of optimal selection underlies the necessity for a sophisticated decision-making framework capable of handling the inherent uncertainty and complexity. This paper introduces an advanced Multi-Criteria Decision-Making (MCDM) methodology that leverages Artificial Intelligence (AI) and Machine Learning (ML) principles, contained within the realms of Complex Circular Intuitionistic Fuzzy Set (C-CIFS) and Dombi Aggregation (DA) Operators. By synthesizing C-CIFS with Dombi operators, we propose a novel aggregation approach characterized by its capability to properly navigate through and aggregate the complicated criteria associated with biometric authentication systems. Our method, the Complex Circular Intuitionistic Fuzzy Dombi Weighted Average (C-CIFDWA) and the Complex Circular Intuitionistic Fuzzy Dombi Weighted Geometric (C-CIFDWG) operators are designed to enhance decision accuracy by effectively managing the nuances of circular intuitionistic fuzzy information. Through a series of comparative studies, including the exploration of radius and complex term impacts, our findings illustrate the superior performance and flexibility of our proposed operators against traditional models. The implementation of our approach within an AI-based framework not only paves the way for more secure and reliable biometric authentication systems but also sets a new standard for decision-making processes in uncertain and imprecise environments. Complex circular intuitionistic fuzzy sets Circular intuitionistic fuzzy sets Complex circular Dombi operations Aggregation operator Biometric Authentication Systems Decision making Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4483111","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":312271254,"identity":"6d91fea1-365e-4577-96f9-1b1d9aa06f11","order_by":0,"name":"Munazza Amin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIie3PsYrCQBCA4QTBas96IYVPIGwIDAgxeZBrNizkGvUFFNyrfIW8hG3qPRa0CaaN2MTeQrsUcjhqKYm5Trj9qynmYxjLMpneuo5lqejXx8n+Vm2JXZ668Y3IlgSRm3T1fWokg2Tyc64uQX+w/Fg7hOTBaqnxytz/rCNQTAWlRLip7sUOoXuRZhGSdTyRtWTMKKMdO9UEHML2AhQSW+om4lWcLcIH4VsB+eElAaq4jpB4bqJUAMWrK9kRhlJtBBK3PEvBocArvOmXzdjbVZfZKM0zhl8EIeRfh/I092vJU9F9k7ddvxX+ZdlkMpn+R1cTB2Vb6l6RaQAAAABJRU5ErkJggg==","orcid":"","institution":"Riphah International University","correspondingAuthor":true,"prefix":"","firstName":"Munazza","middleName":"","lastName":"Amin","suffix":""},{"id":312271255,"identity":"a9f33aad-8123-4582-880d-8af1dc93d0f1","order_by":1,"name":"Kifayat Ullah","email":"","orcid":"","institution":"Riphah International University","correspondingAuthor":false,"prefix":"","firstName":"Kifayat","middleName":"","lastName":"Ullah","suffix":""},{"id":312271256,"identity":"d3c0b593-6ea7-4272-abb5-0ec3009dae02","order_by":2,"name":"Maria Akram","email":"","orcid":"","institution":"Riphah International University","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Akram","suffix":""},{"id":312271257,"identity":"c5d87bdd-ff4e-4de6-904f-742b28a6c049","order_by":3,"name":"Raiha Imran","email":"","orcid":"","institution":"Riphah International University","correspondingAuthor":false,"prefix":"","firstName":"Raiha","middleName":"","lastName":"Imran","suffix":""},{"id":312271258,"identity":"cb43b59b-6238-4394-84d5-fb31248afb25","order_by":4,"name":"Muhammad Safdar Nazeer","email":"","orcid":"","institution":"Riphah International University","correspondingAuthor":false,"prefix":"","firstName":"Muhammad","middleName":"Safdar","lastName":"Nazeer","suffix":""}],"badges":[],"createdAt":"2024-05-27 07:36:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4483111/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4483111/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58427941,"identity":"468ced85-d443-4e7f-80bc-178d310d4784","added_by":"auto","created_at":"2024-06-15 23:01:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":780120,"visible":true,"origin":"","legend":"","description":"","filename":"ComplexCircularIFS27524R.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4483111/v1_covered_1c1c0123-6c14-4f47-ae0c-a4ca4221bdfa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Advancing AI-Based Biometric Authentication in Multi-Criteria Decision Approach Using Complex Circular Intuitionistic Fuzzy Logic and Dombi Operators","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Complex circular intuitionistic fuzzy sets, Circular intuitionistic fuzzy sets, Complex circular Dombi operations, Aggregation operator, Biometric Authentication Systems, Decision making","lastPublishedDoi":"10.21203/rs.3.rs-4483111/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4483111/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the realm of biometric authentication systems, the challenge of optimal selection underlies the necessity for a sophisticated decision-making framework capable of handling the inherent uncertainty and complexity. 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