Multiobjective Design of 2D Hyperchaotic System Using Leader Pareto Grey Wolf Optimizer

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dc.authoridhttps://orcid.org/0000-0002-5229-4018
dc.authorscopusid36728602600
dc.authorwosidGQB-3301-2022
dc.contributor.authorToktaş, Abdurrahim
dc.contributor.authorErkan, Uğur
dc.contributor.authorÜstün, Deniz
dc.contributor.authorLai, Qiang
dc.date.accessioned2024-07-30T13:55:56Z
dc.date.available2024-07-30T13:55:56Z
dc.date.issued2024
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractA chaotic system is a mathematical model exhibiting random and unpredictable behavior. However, existing chaotic systems suffer from suboptimal parameters regarding chaotic indicators. In this study, a novel leader Pareto grey wolf optimizer (LP-GWO) is proposed for multiobjective (MO) design of 2D parametric hyperchaotic system (2D-PHS). The MO capability of LP-GWO is improved by integrating a LP solution within the Pareto optimal set. The effectiveness of LP-GWO is corroborated through a comparison with regular MO versions of grey wolf optimizer (GWO), artificial bee colony, particle swarm optimization, and differential evolution. Additionally, the validation extends to the exploration of LP-GWO's performance across four variants of the 2D-PHS optimized by the compared algorithms. A 2D-PHS model with eight parameters is conceived and then optimized using LP-GWO by ensuring tradeoff between two objectives: Lyapunov exponent (LE) and Kolmogorov entropy (KE). A globally optimal design is chosen for freely improving the two objectives. The chaotic performance of 2D-PHS significantly outperforms existing systems in terms of precise chaos indicators. Therefore, the 2D-PHS has the best ergodicity and erraticity due to optimal parameters provided by LP-GWO.
dc.identifier.citationToktas A., Erkan U., Ustun D., Lai Q.(2024).Multiobjective Design of 2D Hyperchaotic System Using Leader Pareto Grey Wolf Optimizer, IEEE Transactions on Systems, Man, and Cybernetics: Systems, s. 1-11, DOI: 10.1109/TSMC.2024.3401412
dc.identifier.doi10.1109/TSMC.2024.3401412
dc.identifier.endpage11en_US
dc.identifier.issn2168-2216
dc.identifier.issn2168-2232
dc.identifier.scopus2-s2.0-85195386719
dc.identifier.scopusqualityQ1
dc.identifier.startpage1en_US
dc.identifier.urihttps://www.webofscience.com/wos/woscc/full-record/WOS:001242999700001
dc.identifier.urihttps://hdl.handle.net/20.500.13099/297
dc.identifier.wosWOS:001242999700001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorÜstün, Deniz
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofIEEE Transactions on Systems, Man, and Cybernetics: Systems
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectChaos
dc.subjectVectors
dc.subjectChaotic communication
dc.subjectOptimization
dc.subjectPareto optimization
dc.subjectHeuristic algorithms
dc.subjectLinear programming
dc.subjectChaotic system
dc.subjectgrew wolf optimizer
dc.subjectmodified algorithm
dc.subjectPareto optimality
dc.subjectmultiobjective (MO) optimization
dc.titleMultiobjective Design of 2D Hyperchaotic System Using Leader Pareto Grey Wolf Optimizer
dc.typeArticle

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