Grey BP Neural Network Based on Error Grade Iterative and Its Application

摘要：

An improved BP neural network based on grey theory and error grade iterative method is proposed. The accuracy of BP neural network is improved by grey accumulating generation operator reducing the randomness of training samples. Using the grey correlation analysis method to analyze the number of the hidden node for BP neural network, this method realizes the optimization of BP neural network structure. The error grade iterative method improves the convergence speed of BP neural network. At last, it verifies its performance by applying to random drift model of flexible gyroscope and comparing with the normal BP neural network.

关键词： grey system BP neural network error grade iterative

作者: Zhou Jiehua Peng Xiafu

作者单位: School of Information Science and Technology Xiamen University Xiamen 361005, China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering(计算机与通信技术在农业工程国际会议 CCTAE 2010)

会议地点: 成都

会议语种:英文

页码: 81-84

在线出版日期: 2010-06-12（万方平台首次上网日期，不代表论文的发表时间）