On-line Robust Modeling of Nonlinear Systems Using Support Vector Regression

摘要：

To improve robustness of support vector regression (SVR) in nonlinear systems on-line modeling, the relationship between outliers and the robustness of SVR is derived mathematically, and a new modeling method using SVR is proposed. The relationship indicates that the effect of outliers to SVR is decided by the training data distribution and the distance between outliers and the support vectors nearest to them. Therefore, in the method, each component of the training data is normalized into the same range, and then the components representing the system output are compressed differently to change the training data distribution to reduce the effects of the outliers. Meanwhile, a data updating criterion is presented to eliminate outliers. The method is applied to multichannel electrohydraulic force servo synchronous loading system to predict the load output, and the results show its effectiveness.

关键词： support vector regression robust outlier

作者: Li Dahai Li Tianshi

作者单位: School of Mechanical Engineering Xian Jiaotong University Xian, China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 204-208

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）