文章基本信息

标题：Improved Artificial Fish Algorithm for Parameters Optimization of PID Neural Network
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作者：Wang, Jing ; Huang, Yourui
期刊名称：Journal of Networks
印刷版ISSN：1796-2056
出版年度：2013
卷号：8
期号：8
页码：1726-1733
DOI：10.4304/jnw.8.8.1726-1733
语种：English
出版社：Academy Publisher
摘要：In order to solve problems such as initial weights are difficult to be determined, training results are easy to trap in local minima in optimization process of PID neural network parameters by traditional BP algorithm, this paper proposed a new method based on improved artificial fish algorithm for parameters optimization of PID neural network. This improved artificial fish algorithm uses a composite adaptive artificial fish algorithm based on optimal artificial fish and nearest artificial fish to train network weights parameters of PID neural network. By comparing food consistence in preying behavior to adaptively select vision and step of artificial fish, this method overcomes shortcomings such as slow convergence speed, low optimization accuracy of basic artificial fish algorithm. Simulations of PID neural network system whose parameters are trained respectively through BP algorithm and improved artificial fish algorithm are conducted respectively in the MATLAB environment. The simulation result shows that the PID neural network control system whose parameters are trained by the improved artificial fish algorithm has a better control effect, especially for nonlinear systems
关键词：Improved Artificial Fish Algorithm;PID Neural Network;Parameters Optimization;Control Effect