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

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...

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Main Authors: Zuoquan Zhang, Fan Lang, Qin Zhao
Format: Article
Language:English
Published: Wiley 2009-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2009/830572
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author Zuoquan Zhang
Fan Lang
Qin Zhao
author_facet Zuoquan Zhang
Fan Lang
Qin Zhao
author_sort Zuoquan Zhang
collection DOAJ
description 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.
format Article
id doaj-art-84ebf6ab42c24710815ffa6c8f6dfd69
institution Kabale University
issn 1026-0226
1607-887X
language English
publishDate 2009-01-01
publisher Wiley
record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-84ebf6ab42c24710815ffa6c8f6dfd692025-08-20T03:37:12ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2009-01-01200910.1155/2009/830572830572Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic AlgorithmsZuoquan Zhang0Fan Lang1Qin Zhao2School of Sciences, Beijing Jiaotong University, 100044 Beijing, ChinaSchool of Sciences, Beijing Jiaotong University, 100044 Beijing, ChinaSchool of Economics and Management, Beijing Jiaotong University, Beijing 100044, ChinaA 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.http://dx.doi.org/10.1155/2009/830572
spellingShingle Zuoquan Zhang
Fan Lang
Qin Zhao
Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms
Discrete Dynamics in Nature and Society
title Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms
title_full Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms
title_fullStr Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms
title_full_unstemmed Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms
title_short Research of Financial Early-Warning Model on Evolutionary Support Vector Machines Based on Genetic Algorithms
title_sort research of financial early warning model on evolutionary support vector machines based on genetic algorithms
url http://dx.doi.org/10.1155/2009/830572
work_keys_str_mv AT zuoquanzhang researchoffinancialearlywarningmodelonevolutionarysupportvectormachinesbasedongeneticalgorithms
AT fanlang researchoffinancialearlywarningmodelonevolutionarysupportvectormachinesbasedongeneticalgorithms
AT qinzhao researchoffinancialearlywarningmodelonevolutionarysupportvectormachinesbasedongeneticalgorithms