High-precision parameter identification for the lorenz system via starfish optimization algorithm

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dc.contributor.authorEkinci, Serdar
dc.contributor.authorTürkeri, Cebrail
dc.contributor.authorİzci, Davut
dc.contributor.authorKiselychnyk, Oleh
dc.contributor.authorBektaş Güneş, Burcu
dc.date.accessioned2025-12-25T12:39:16Z
dc.date.available2025-12-25T12:39:16Z
dc.date.issued2025
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description9th International Artificial Intelligence and Data Processing Symposium, IDAP 2025, 6-7 September 2025, Malatya
dc.description.abstractParameter estimation plays a vital role in the accurate modeling and control of chaotic systems due to their inherent sensitivity to initial conditions and system parameters. This study introduces a novel approach for parameter identification in the Lorenz system using the starfish optimization algorithm (SFOA). The problem is formulated as a nonlinear optimization task, and the SFOA is employed to minimize the discrepancy between the observed and simulated trajectories. The proposed method is evaluated across multiple independent runs and benchmarked against several well-known optimization techniques. The results demonstrate that the SFOA achieves highly accurate and consistent parameter estimates, exhibiting superior robustness and convergence behavior compared to other methods. These findings suggest that SFOA is a promising candidate for addressing parameter estimation challenges in chaotic and nonlinear dynamical systems.
dc.identifier.doi10.1109/IDAP68205.2025.11222371
dc.identifier.isbn9798331589905
dc.identifier.scopus2-s2.0-105024994328
dc.identifier.urihttps://doi.org/10.1109/IDAP68205.2025.11222371
dc.identifier.urihttps://hdl.handle.net/11501/2576
dc.indekslendigikaynakScopus
dc.institutionauthorBektaş Güneş, Burcu
dc.institutionauthorid0000-0002-9046-1542
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof9th International Artificial Intelligence and Data Processing Symposium, IDAP 2025
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectChaotic Systems
dc.subjectMetaheuristics
dc.subjectParameter Identification
dc.subjectStarfish Optimization Algorithm
dc.titleHigh-precision parameter identification for the lorenz system via starfish optimization algorithm
dc.typeConference Object

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