Discrete Dynamics in Nature and Society
Volume 2009 (2009), Article ID 830572, 8 pages
Research Article

Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms

1School of Sciences, Beijing Jiaotong University, 100044 Beijing, China
2School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China

Received 7 September 2009; Accepted 12 October 2009

Academic Editor: Guang Zhang

Copyright © 2009 Zuoquan Zhang et al. 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.


A support vector machine is a new learning machine; it is based on the statistics learning theory and attracts the attention of all researchers. Recently, the support vector machines (SVMs) have been applied to the problem of financial early-warning prediction (Rose, 1999). The SVMs-based method has been compared with other statistical methods and has shown good results. But the parameters of the kernel function which influence the result and performance of support vector machines have not been decided. Based on genetic algorithms, this paper proposes a new scientific method to automatically select the parameters of SVMs for financial early-warning model. The results demonstrate that the method is a powerful and flexible way to solve financial early-warning problem.