Hybrid Neural Network Bankruptcy Prediction: An Integration of Financial Ratios, Intellectual Capital Ratios, MDA, and Neural Network Learning

DOI

10.2991/jcis.2006.323How to use a DOI?

Keywords

Bankruptcy prediction; Neural network; Hybrid neural network; MDA

Abstract

One purpose of this paper is to propose hybrid neural network models for bankruptcy prediction. The proposed hybrid neural network models are, respecitvely, a MDA model integrated with financial ratios, a MDA model integrated with financial ratios and intellectual capital ratios, a MDA-assisted neural network model integrated with financial ratios, and a MDA-assissted neural network model integrated with financial ratios and intellectual capital ratios. The performance of the hybrid neural network model is compared with MDA model integrated with financial ratios as a benchmark. Empirical results using Taiwan bankruptcy data show that hybrid neural network models are very promising ones in terms of accuracy and adaptability.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wen-Kuei Hsieh
AU  - Shang-Ming Liu
AU  - Sung-Yi Hsieh
PY  - 2006/10
DA  - 2006/10
TI  - Hybrid Neural Network Bankruptcy Prediction: An Integration of Financial Ratios, Intellectual Capital Ratios, MDA, and Neural Network Learning
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.323
DO  - 10.2991/jcis.2006.323
ID  - Hsieh2006/10
ER  -