Wavelet Neural Networks and Support Vector Machine for Financial Distress Prediction Modelling: The Chinese Case

被引：0

作者：

Yao, Hongshan ^{[1
]}

机构：

[1] Zhongnan Univ Econ & Law, Wuhan 430074, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 2, PROCEEDINGS | 2009年 / 5552卷

关键词：

Wavelet neural networks; Support vector machine; Financial distress;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Wavelet neural networks (WNN) and Support vector machine (SVM) are two advanced methods which are fit for classification. A comparative analysis of the two methods was conducted based on Chinese firms. The results show WNN has good classification effect. Wavelet decomposition has been demonstrated to be an effective tool for recognizing the firms' feature. Also the Study applied SVM to the same estimation sample and test sample. The results show SVM is much superior to WNN for small sample learning.

引用

页码：416 / 423

页数：8

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