An Improved Cuckoo Search Optimization Algorithm for the Problem of Chaotic Systems Parameter Estimation

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Abstract

This paper proposes an improved cuckoo search (ICS) algorithm to establish the parameters of chaotic systems. In order to improve the optimization capability of the basic cuckoo search (CS) algorithm, the orthogonal design and simulated annealing operation are incorporated in the CS algorithm to enhance the exploitation search ability. Then the proposed algorithm is used to establish parameters of the Lorenz chaotic system and Chen chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the algorithm can estimate parameters with high accuracy and reliability. Finally, the results are compared with the CS algorithm, genetic algorithm, and particle swarm optimization algorithm, and the compared results demonstrate the method is energy-efficient and superior.

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Wang, J., Zhou, B., & Zhou, S. (2016). An Improved Cuckoo Search Optimization Algorithm for the Problem of Chaotic Systems Parameter Estimation. Computational Intelligence and Neuroscience, 2016. https://doi.org/10.1155/2016/2959370

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