Prediction of gyro motors state based on grey model and BP neural network

摘要：

The prediction accuracy of grey theory was limited by its high requirement of datas smoothness. BP neural is adept in solving nonlinear problem and performs well in self adaption and self organization, but its training effect and efficiency was limited by the number of data. A hybrid model combined advantages of grey theory and BP neural network is put forward based on analysis of gyro motors state parameters. And then, grey theory, BP neural network and the hybrid model were constructed respectively to model and predict the parameters. The results prove the validity and accuracy of hybrid model.

关键词： gyro motor grey theory BP neural network hybrid model

作者: ZHA Feng HU Bai-qing

作者单位: Navigation engineering department The engineering university of navy Wuhan, China

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 2013-2016

在线出版日期: 2009-10-10（万方平台首次上网日期，不代表论文的发表时间）