Time Series Prediction for Machining Errors Using Support Vector Regression

摘要：

A time series prediction method using support vector regression(SVR)for machining errors is presented in this paper.The design steps and learning algorithm are also addressed.Since SVR have greater generalization ability and guarantee global minima for given training data,it is believed that SVR will perform well for time series for machining errors.A typical machining process of cutting bearing outer race is carried out and the real measured data are used to contrast experiment.The experimental results demonstrate the feasibility of applying SVR in machining errors prediction and prove that SVR is applicable and performs well for small-batch machining process analysis.

作者: Deh Wu

作者单位: Key Laboratory of Numerical Control of Jiangxi Province,Jiujiang University,Jiujiang 332005

会议类型: 国际会议

会议名称: 第一届智能网络与智能系统国际会议(ICINIS 2008)(The First International Conference on Intelligent Networks and Intelligent Systems)

会议地点: 武汉

会议语种:英文

在线出版日期: 2008-11-01（万方平台首次上网日期，不代表论文的发表时间）