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Chaotic invasive weed optimization algorithm with application to parameter estimation of chaotic systems

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  • Ahmadi, Mohamadreza
  • Mojallali, Hamed

Abstract

This paper introduces a novel hybrid optimization algorithm by taking advantage of the stochastic properties of chaotic search and the invasive weed optimization (IWO) method. In order to deal with the weaknesses associated with the conventional method, the proposed chaotic invasive weed optimization (CIWO) algorithm is presented which incorporates the capabilities of chaotic search methods. The functionality of the proposed optimization algorithm is investigated through several benchmark multi-dimensional functions. Furthermore, an identification technique for chaotic systems based on the CIWO algorithm is outlined and validated by several examples. The results established upon the proposed scheme are also supplemented which demonstrate superior performance with respect to other conventional methods.

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  • Ahmadi, Mohamadreza & Mojallali, Hamed, 2012. "Chaotic invasive weed optimization algorithm with application to parameter estimation of chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 45(9), pages 1108-1120.
    • Handle: RePEc:eee:chsofr:v:45:y:2012:i:9:p:1108-1120
    DOI: 10.1016/j.chaos.2012.05.010
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    2. Mousavi, Yashar & Alfi, Alireza, 2018. "Fractional calculus-based firefly algorithm applied to parameter estimation of chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 202-215.
    3. Bezruchko, B.P. & Ponomarenko, V.I. & Smirnov, D.A. & Sysoev, I.V. & Prokhorov, M.D., 2021. "Class-oriented techniques for reconstruction of dynamics from time series," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).

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