Parameter optimization of chaotic system using Pareto-based triple objective artificial bee colony algorithm

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dc.authorid0000-0002-5229-4018
dc.authorscopusid36728602600
dc.authorwosidGQB-3301-2022
dc.contributor.authorToktaş, Abdurrahim
dc.contributor.authorErkan, Uğur
dc.contributor.authorÜstün, Deniz
dc.contributor.authorWang, Xingyuan
dc.date.accessioned2023-08-10T11:13:54Z
dc.date.available2023-08-10T11:13:54Z
dc.date.issued2023
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractChaotic map is a kind of discrete chaotic system. The existing chaotic maps suffer from optimal parameters in terms of chaos measurements. In this study, a novel approach of optimization of parametric chaotic map (PCM) using triple objective optimization is presented for the first time. A PCM with six parameters is first conceived and then optimized using Pareto-based triple objective artificial bee colony (PT-ABC) algorithm. Pareto optimality is employed to catch the trade-off among the objectives: Lyapunov exponent (LE), sample entropy (SE), and Kolmogorov entropy (KE). A global optimal design including the six parameters is selected for minimizing the reciprocal of the three objectives independently. The chaotic performance of PCM is verified through an evaluation with bifurcation diagram, attractor, LE, SE, KE, and correlation dimension. The results are also validated by comparison with those of which reported elsewhere. Furthermore, the applicability of PCM is examined over image encryption and the results are compared with existing chaos-based IEs. Therefore, the PCM manifests the best ergodicity and complexity thanks to its PT-ABC algorithm.
dc.identifier.citationToktas, A., Erkan, U., Ustun, D. ve Xingyuan, W. (2023). Parameter optimization of chaotic system using Pareto-based triple objective artificial bee colony algorithm. Neural Computing and Applications 35, 13207–13223. https://doi.org/10.1007/s00521-023-08434-y
dc.identifier.doi10.1007/s00521-023-08434-y
dc.identifier.endpage13223en_US
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.issue18en_US
dc.identifier.scopus2-s2.0-85149758719
dc.identifier.scopusqualityQ1
dc.identifier.startpage13207en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-023-08434-y
dc.identifier.urihttps://hdl.handle.net/20.500.13099/157
dc.identifier.volume35en_US
dc.identifier.wosWOS:000947298400007
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorÜstün, Deniz
dc.language.isoen
dc.publisherSpringer London Ltd
dc.relation.ispartofNeural Computing and Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectChaotic system
dc.subjectImage encryption
dc.subjectMulti-objective optimization
dc.subjectPareto optimization
dc.subjectComputational complexity
dc.subjectCryptography
dc.subjectPareto principle
dc.subjectParameter estimation
dc.subjectLyapunov methods
dc.subjectImage processing
dc.subjectEntropy
dc.subjectEconomic and social effects
dc.subjectSample entropy
dc.subjectParameter optimization
dc.subjectArtificial bees
dc.subjectMulti-objectives optimization
dc.subjectLyapunov exponent
dc.subjectKolmogorov entropies
dc.subjectImages encryptions
dc.subjectChaotic map
dc.subjectBee colony algorithms
dc.subjectMultiobjective optimization
dc.titleParameter optimization of chaotic system using Pareto-based triple objective artificial bee colony algorithm
dc.typeArticle

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