Fractional-order chaotic oscillator-based Aquila optimization algorithm for maximization of the chaotic with Lorentz oscillator
Küçük Resim Yok
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer London Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The random structures in the Aquila optimization algorithm are modeled with fractional chaotic oscillators, and the fractional-order chaotic oscillator-based Aquila optimization (FOCOBAO) algorithm was suggested in this study. First of all, the basic AO algorithm was examined. In particular, random variables that affect the optimization performance of the AO algorithm have been determined. Then, instead of the determined random variables, the coefficients were derived with fractional chaotic oscillators and used in the FOCOBAO. The superiority of the proposed algorithm was primarily demonstrated via twenty-three benchmark functions. The results were matched with GO, EO, GWO, MPA, WOA, SMA and basic AO optimization algorithms. Then, the design of the Lorenz chaotic oscillator, according to maximum chaotic objective function, is a topic that remains up to date in the literature. In this study, a fractional chaotic Lorenz oscillator was designed with FOCOBAO as an engineering application. Especially for maximum chaoticity, maximum positive Lyapunov exponents were determined. In this way, a different design process has been proposed in the literature. The basic AO algorithm, which includes stochastic processes, was developed with fractional chaotic oscillators, and a deterministic method was obtained. The parameters of the Lorenz system were calculated for maximum chaoticity, and the results were presented comparatively.
Açıklama
Anahtar Kelimeler
Fractional-order chaotic oscillator, Aquila optimization algorithm, Lorenz system
Kaynak
Neural Computing & Applications
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
35
Sayı
29
