Mechanical and Electrical Device Condition Trend Prediction Based on GA-SVR

摘要：

　　This paper mainly discuss three kinds of optimization method to get the optimal penalty factor C and kernel parameter G of support vector regression.the mean square error MSE, correlation coefficient R, the number of support vector nsv was regarded as indexes to measure the merits of the various optimization prediction model the experimental results shows that the prediction model based on genetic optimization is closer to the actual value in the prediction of vibration intensity, and prediction performance is better than other optimization methods.It also shows the prediction model has a good predictive ability on the condition trend of mechanical and electrical device.

关键词： genetic optimization SVR PSO MSE trend prediction

作者: Lu Zhengchun Xing Jishou

作者单位: School of Mechanical and Electrical Engineering,Beijing Information Science &Technology University,100192,Beijing

会议类型: 国际会议

会议名称: 2013 IEEE 11th International Conference on Electronic Measurement & Instruments(第十一届IEEE国际电子测量与仪器学术会议)

会议地点: 哈尔滨

会议语种:英文

页码: 49-52

在线出版日期: 2013-08-16（万方平台首次上网日期，不代表论文的发表时间）