title: An Improved Cuckoo Search Optimization Algorithm for the Problem of Chaotic Systems Parameter Estimation.
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.
authors.affiliation: National Key Laboratory on Electromagnetic Environmental Effects and Electro-Optical Engineering, PLA University of Science and Technology, Nanjing 210007, China.
authors.forename: Jun
authors.initials: J
authors.lastname: Wang
authors.affiliation: National Key Laboratory on Electromagnetic Environmental Effects and Electro-Optical Engineering, PLA University of Science and Technology, Nanjing 210007, China.
authors.forename: Bihua
authors.initials: B
authors.lastname: Zhou
authors.affiliation: College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China.
authors.forename: Shudao
authors.initials: S
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D000818:Animals; D001717:Birds / Q000502:physiology; D003198:Computer Simulation; D005106:Exploratory Behavior / Q000502:physiology*; D006801:Humans; D008962:Models, Theoretical; D017711:Nonlinear Dynamics