文献类型：期刊文献

英文题名：Tuning the structure and parameters of a neural network using cooperative binary-real particle swarm optimization

作者：Zhao, Liang[1];Qian, Feng[1]

机构：[1]E China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2011

卷号：38

期号：5

起止页码：4972

外文期刊名：EXPERT SYSTEMS WITH APPLICATIONS

收录：;EI(收录号：20110513630384);WOS:【SCI-EXPANDED(收录号:WOS:000287419900035)】；

基金：The authors are grateful to the anonymous reviewers for their helpful comments and constructive suggestions with regard to this paper. Financial support of National Science Fund for Distinguished Young Scholars (No. 60625302), National High-Tech Research and Development Program of China (No. 2009AA04Z159), National Basic Research Program of China (No. 2009CB320603), National Natural Science Foundation of China (No. 60804029), PCSIRT (No. IRT0721), 111 Project (No. B08021), Shanghai Key Technologies R&D Program (No. 08DZ1123100, 09DZ1120400 and 10JC1403400), Shanghai international cooperation project (No. 08160710500) and the Shanghai Leading Academic Discipline Project (No. B504) are acknowledged.

语种：英文

外文关键词：Particle swarm optimization; Neural network; Cooperative

摘要：In this paper, a cooperative binary-real particle swarm optimization is applied to tune the structure and parameters of a neural network. A neural network with switches of its links, which is used to decide whether there is a link between two neurons or not, is introduced firstly. Thus, the structure of a neural network can be decided by the switches. A cooperative binary-real particle swarm optimization algorithm is utilized to find the compact structures and optimal parameters of the proposed neural network. The number of hidden nodes of the neural network is increased from a small number until its learning ability is achieved. The simulation experiments indicate that the proposed approach can obtain better results than the existing approaches in recent literature. (C) 2010 Elsevier Ltd. All rights reserved.