Unifying optimization forces: Harnessing the fine-structure constant in an electromagnetic-gravity optimization framework

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dc.authorscopusidKorhan Cengiz / 56522820200
dc.authorwosidKorhan Cengiz / HTN-8060-2023
dc.contributor.authorAkhtar, Md Amir Khusru
dc.contributor.authorKumar, Mohit
dc.contributor.authorVerma, Sahil
dc.contributor.authorCengiz, Korhan
dc.contributor.authorVerma, Pawan Kumar
dc.contributor.authorKhurma, Ruba Abu
dc.contributor.authorAlazab, Moutaz
dc.date.accessioned2025-04-16T14:05:17Z
dc.date.available2025-04-16T14:05:17Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü
dc.description.abstractThe electromagnetic-gravity optimization (EMGO) framework is a novel optimization technique that integrates the fine-structure constant and leverages electromagnetism and gravity principles to achieve efficient and robust optimization solutions. Through comprehensive performance evaluation and comparative analyses against state-of-the-art optimization techniques, EMGO demonstrates superior convergence speed and solution quality. Its unique balance between exploration and exploitation, enabled by the interplay of electromagnetic and gravity forces, makes it a powerful tool for finding optimal or near-optimal solutions in complex problem landscapes. The research contributes by introducing EMGO as a promising optimization approach with diverse applications in engineering, decision support systems, machine learning, data mining, and financial optimization. EMGO's potential to revolutionize optimization methodologies, handle real-world problems effectively, and balance global exploration and local exploitation establishes its significance. Future research opportunities include exploring adaptive mechanisms, hybrid approaches, handling high-dimensional problems, and integrating machine learning techniques to enhance its capabilities further. EMGO gives a novel approach to optimization, and its efficacy, advantages, and potential for extensive adoption open new paths for advancing optimization in many scientific, engineering, and real-world domains.
dc.description.sponsorshipQatar National Library
dc.identifier.citationAkhtar, M. A. K., Kumar, M., Verma, S., Cengiz, K., Verma, P. K., Khurma, R. A., & Alazab, M. (2024). Unifying optimization forces: Harnessing the fine-structure constant in an electromagnetic-gravity optimization framework. Journal of Intelligent Systems, 33(1), 20230306.
dc.identifier.doi10.1515/jisys-2023-0306
dc.identifier.endpage19
dc.identifier.issn0334-1860
dc.identifier.issn2191-026X
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85213011149
dc.identifier.scopusqualityQ2
dc.identifier.startpage1
dc.identifier.urihttp://dx.doi.org/10.1515/jisys-2023-0306
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6042
dc.identifier.volume33
dc.identifier.wosWOS:001379454500001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorCengiz, Korhan
dc.institutionauthoridKorhan Cengiz / 0000-0001-6594-8861
dc.language.isoen
dc.publisherWalter de gruyter gmbh
dc.relation.ispartofJournal of intelligent systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectConvergence Speed
dc.subjectElectromagnetism
dc.subjectFine-Structure Constant
dc.subjectGravity
dc.subjectOptimization Technique
dc.titleUnifying optimization forces: Harnessing the fine-structure constant in an electromagnetic-gravity optimization framework
dc.typeArticle

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