文章基本信息

标题：Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms
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作者：Zuoquan Zhang ; Fan Lang ; Qin Zhao 等
期刊名称：Discrete Dynamics in Nature and Society
印刷版ISSN：1026-0226
电子版ISSN：1607-887X
出版年度：2009
卷号：2009
DOI：10.1155/2009/830572
出版社：Hindawi Publishing Corporation
摘要：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.