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Computers & Operations Research
Volume 32, Issue 5, May 2005, Pages 1115-1129
 
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doi:10.1016/j.cor.2003.09.015    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2003 Published by Elsevier Ltd.

An application of pattern recognition on scoring Chinese corporations financial conditions based on backpropagation neural network

Liang LiangCorresponding Author Contact Information, E-mail The Corresponding Author and Desheng WuE-mail The Corresponding Author

School of Business, University of Science and Technology of China, Hefei Anhui 230026, PR China

Available online 14 November 2003.

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Abstract

The paper follows three parts on the whole. The first part reviews the literature on financial diagnosis and the appropriate measures to be currently used. Thus the research gaps in the fields are highlighted. Next part details the variables and samples selection, data, analysis and results applying to scoring financial conditions of a Chinese corporation. By using pattern recognition theory, a scoring model is developed to analyze corporate financial conditions by backpropagation neural networks. It has been proved to be better than ordinary BPNN and traditional multivariate discriminant analysis. Finally, conclusions are presented.

Author Keywords: Pattern recognition; Backpropagation neural network; Multivariate discriminant analysis; Financial diagnosis

Article Outline

1. Introduction
2. Sample design and variable selection
2.1. Sample design
2.1.1. Sample-design criterion
2.1.2. Sample selection
2.2. Variable selection
3. Model development
3.1. Optimization design of algorithm
3.2. Pattern transformation
3.3. ANN model
4. Testing and comparison of scoring power
4.1. Testing and comparison of initial pattern and rotated pattern
4.2. Comparison of rotated BPNN and MDA
5. Summary and conclusions
Acknowledgements
Appendix
References



 
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