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Neuro-genetic approach for bankruptcy prediction modeling

Title
Neuro-genetic approach for bankruptcy prediction modeling
Authors
Shin K.-S.Lee K.J.
Ewha Authors
신경식
SCOPUS Author ID
신경식scopus
Issue Date
2004
Journal Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN
0302-9743JCR Link
Citation
vol. 3214, pp. 646 - 652
Indexed
SCOPUS scopus
Abstract
Artificial neural network (ANN) modeling has become the dominant modeling paradigm for bankruptcy prediction. To further improve the neural network's prediction capability, the integration of the ANN models and the hybridization of ANN with relevant paradigms such as evolutionary computing has been demanded. This paper first attempted to apply neuro-genetic approach to bankruptcy prediction problem for finding optimal weights and confirmed that the approach can be a good methodology though it currently could not outperform the backpropagation learning algorithm. The result of this paper shows a possibility of neuro-genetic approach to bankruptcy prediction problem since the simple neuro-genetic approach produced a meaningful performance. © Springer-Verlag 2004.
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경영대학 > 경영학전공 > Journal papers
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