期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 38, 期 12, 页码 15103-15109出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2011.05.011
关键词
Parameter estimation; Chaotic systems; Biogeography-based optimization; Hybrid algorithm
类别
资金
- NSFC [60774082, 70871065, 60834004]
- Program for New Century Excellent Talents in University [NCET-10-0505]
- Doctoral Program Foundation of Institutions of Higher Education of China [20100002110014]
Parameter estimation of chaotic systems is an important issue in the fields of computational mathematics and nonlinear science, which has gained increasing research and applications. In this paper, biogeography-based optimization (BBO), a new effective optimization algorithm based on the biogeography theory of the geographical distribution of biological organisms, is reasonably combined with differential evolution and simplex search to develop an effective hybrid algorithm for solving parameter estimation problem that is formulated as a multi-dimensional optimization problem. By suitably fusing several optimization methods with different searching mechanisms and features, the exploration and exploitation abilities of the hybrid algorithm can be enhanced and well balanced. Numerical simulation based on several typical chaotic systems and comparisons with some existing methods demonstrate the effectiveness of the proposed algorithm. In addition, the effects of population size and noise on the performances of the hybrid algorithm are investigated. (C) 2011 Elsevier Ltd. All rights reserved.
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