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    Fractional-order chaotic oscillator-based Aquila optimization algorithm for maximization of the chaotic with Lorentz oscillator
    (Springer London Ltd, 2023) Cavlak, Yakup; Ates, Abdullah; Abualigah, Laith; Elaziz, Mohammed Abd
    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.