Abstract
Parameter estimation for chaotic system is, in fact, a multi-dimensional optimization problem. By combining biogeography-based optimization (BBO) with harmony search (HS) and opposition-based learning (OBL), a hybrid BBO scheme is proposed for solving the chaotic parameter estimation problem. The HS is used to enhance the local search ability of BBO, and OBL is employed to increase the diversity of the initial population, thereby improving the optimizing performance. The effectiveness and robustness of the proposed scheme are verified by numerical simulations on two typical chaotic systems.
Publisher
Acta Physica Sinica, Chinese Physical Society and Institute of Physics, Chinese Academy of Sciences
Subject
General Physics and Astronomy
Reference17 articles.
1. Maybhate A, Amritkar R E 1999 Phys. Rev. E 59 284
2. Saha P, Banerjee S, Chowdhury A R 2004 Phys. Lett. A 326 133
3. Xu D L, Lu F F 2005 Chaos Soliton. Fract. 25 361
4. Fotsina H B, Woafob P 2005 Chaos Soliton. Fract. 24 1363
5. Peng H P, Li L X, Yang Y X, Zhang X H, Gao Y 2007 Acta Phys. Sin. 56 6246 (in Chinese) [彭海朋, 李丽香, 杨义先, 张小红, 高洋 2007 物理学报 56 6246]
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献