Parameter identification of chaotic systems using evolutionary programming approach

Jen F. Chang; Yi Sung Yang; Teh-Lu Liao; Jun J. Yan

doi:10.1016/j.eswa.2007.09.021

Parameter identification of chaotic systems using evolutionary programming approach

Jen F. Chang, Yi Sung Yang, Teh-Lu Liao, Jun J. Yan

Department of Engineering Science

Research output: Contribution to journal › Article › peer-review

48 Citations (Scopus)

Abstract

This paper is concerned with the parameter identification problem for chaotic systems. An evolutionary programming (EP) approach is newly introduced to solve this problem. The unknown parameters of chaotic systems are taken as a parameter vector, and will be optimally approximated to the exact values of parameters by using the proposed EP algorithm. The unified chaotic systems including Lorenz, Lü and Chen systems are used in an illustrative example to show the validity of the proposed method.

Original language	English
Pages (from-to)	2074-2079
Number of pages	6
Journal	Expert Systems With Applications
Volume	35
Issue number	4
DOIs	https://doi.org/10.1016/j.eswa.2007.09.021
Publication status	Published - 2008 Nov 1

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Science Applications

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abstract = "This paper is concerned with the parameter identification problem for chaotic systems. An evolutionary programming (EP) approach is newly introduced to solve this problem. The unknown parameters of chaotic systems are taken as a parameter vector, and will be optimally approximated to the exact values of parameters by using the proposed EP algorithm. The unified chaotic systems including Lorenz, L{\"u} and Chen systems are used in an illustrative example to show the validity of the proposed method.",

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