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Fractional calculus-based firefly algorithm applied to parameter estimation of chaotic systems

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  • Mousavi, Yashar
  • Alfi, Alireza

Abstract

This paper deals with the parameters estimation problem of chaotic systems using firefly algorithm (FA). The main contribution of the present work is to introduce a modified version of FA by incorporating fractional calculus during the search process, namely fractional-order FA (FOFA). FOFA simulates the behavior of each firefly with more historical memory, leading to enhance the performance of the basic FA by controlling its convergence speed. A simple structure and straightforward to implement are the main aspects of the proposed FOFA. First, the capability of FOFA is evaluated on the well-known test functions adopted from CEC'2015. Then, FOFA is applied for parameter estimation of chaotic systems. Results reveal that the incorporation of a memory term into the FA is an extremely significant development in comparison with other types of FAs.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:chsofr:v:114:y:2018:i:c:p:202-215
    DOI: 10.1016/j.chaos.2018.07.004
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    References listed on IDEAS

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    Cited by:

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    2. Abedi Pahnehkolaei, Seyed Mehdi & Alfi, Alireza & Tenreiro Machado, J.A., 2022. "Analytical stability analysis of the fractional-order particle swarm optimization algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
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    8. Cui, Yibing & Hu, Wei & Rahmani, Ahmed, 2023. "Fractional-order artificial bee colony algorithm with application in robot path planning," European Journal of Operational Research, Elsevier, vol. 306(1), pages 47-64.

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