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Parameter estimation for chaotic systems by hybrid differential evolution algorithm and artificial bee colony algorithm

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Abstract

This paper is concerned with the parameter estimation of nonlinear chaotic system, which could be essentially formulated as a multi-dimensional optimization problem. In this paper, a hybrid algorithm by combining differential evolution with artificial bee colony is implemented to solve parameter estimation for chaotic systems. Hybrid algorithm combines the exploration of differential evolution with the exploitation of the artificial bee colony effectively. Experiments have been conducted on Lorenz system and Chen system. The proposed algorithm is applied to estimate the parameters of two chaotic systems. Simulation results and comparisons demonstrate that the proposed algorithm is better or at least comparable to differential evolution, artificial bee colony, particle swarm optimization, and genetic algorithm from literature when considering the quality of the solutions obtained.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant Nos. 61370052, 61370156, and 11226275; Natural Science Foundation of Jilin Province under Grant No. 201215006; and Program for New Century Excellent Talents in University under Grant NCET-13-0724. We thank Quan Liu for correcting the English in this manuscript.

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  1. School of Computer Science and Information Technology, Northeast Normal University, Changchun, 130117, China

    Xiangtao Li & Minghao Yin

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  1. Xiangtao Li
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  2. Minghao Yin
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Correspondence to Minghao Yin.

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Li, X., Yin, M. Parameter estimation for chaotic systems by hybrid differential evolution algorithm and artificial bee colony algorithm. Nonlinear Dyn 77, 61–71 (2014). https://doi.org/10.1007/s11071-014-1273-9

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  • DOI: https://doi.org/10.1007/s11071-014-1273-9

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