The Application of Imperialist Competitive Algorithm based on Chaos Theory in Perceptron Neural Network

摘要：

In this paper, the weights of a Neural Network using Chaotic Imperialist Competitive Algorithm are updated. A three-layered Perseptron Neural Network applied for prediction of the maximum worth of the stocks changed in TEHRANS bourse market. We trained this neural network with CICA, ICA, PSO and GA algorithms and compared the results with each other. The consideration of the results showed that the training and test error of the network trained by the CICA algorithm has been reduced in comparison to the other three methods.

关键词： Imperialist Competitive Algorithm Perceptron Neural Network chaotic

作者: Xiuping Zhang

作者单位: Department of Computer Science Tonghua Normal University,Tonghua, 134002 China

会议类型: 国际会议

会议名称: 2010 Second Asia-Pacific Conference on Information Processing(2010年第二届亚太地区信息处理国际会议 APCIP 2010)

会议地点: 南昌

会议语种:英文

页码: 307-310

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）