Parameter estimation for chaotic systems based on improved boundary chicken swarm optimization

被引：2
|
作者：
Chen, Shaolong [1 ]
Yan, Renhuan [1 ]
机构：
[1] Jinan Univ, Coll Informat Sci & Technol, Guangzhou 510632, Guangdong, Peoples R China
来源：
INFRARED TECHNOLOGY AND APPLICATIONS, AND ROBOT SENSING AND ADVANCED CONTROL | 2016年 / 10157卷
关键词：
Chicken swarm optimization; Chaotic system; Parameter estimation; Lorenz system; Cross-border processing; Intelligent optimization algorithm; Particle group optimization; Genetic algorithm; Convergence rate; Convergence precision; ALGORITHM;
D O I：
10.1117/12.2246548
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Estimating unknown parameters for chaotic system is a key problem in the field of chaos control and synchronization. Through constructing an appropriate fitness function, parameter estimation of chaotic system could be converted to a multidimensional parameter optimization problem. In this paper, a new method base on improved boundary chicken swarm optimization (IBCSO) algorithm is proposed for solving the problem of parameter estimation in chaotic system. However, to the best of our knowledge, there is no published research work on chicken swarm optimization for parameters estimation of chaotic system. Computer simulation based on Lorenz system and comparisons with chicken swarm optimization, particle swarm optimization and genetic algorithm shows the effectiveness and feasibility of the proposed method.
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收藏
页数：6
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