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Mathematical Problems in Engineering
Volume 2014, Article ID 373571, 5 pages
Research Article

Robust ε-Support Vector Regression

School of Mechanical Engineering, Northwestern Polytechnical University, Mailbox 301, No. 127 Youyi Road, Xi’an, Shaanxi 710072, China

Received 1 August 2013; Revised 25 November 2013; Accepted 25 November 2013; Published 20 February 2014

Academic Editor: Andrzej Swierniak

Copyright © 2014 Yuan Lv and Zhong Gan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Spheroid disturbance of input data brings great challenges to support vector regression; thus it is essential to study the robust regression model. This paper is dedicated to establish a robust regression model which makes the regression function robust against disturbance of data and system parameter. Firstly, two theorems have been given to show that the robust linear ε-support vector regression problem could be settled by solving the dual problems. Secondly, it has been focused on the development of robust support vector regression algorithm which is extended from linear domain to nonlinear domain. Finally, the numerical experiments result demonstrates the effectiveness of the models and algorithms proposed in this paper.