Comparative analysis of artificial neural network models: Application in bankruptcy prediction

Comparative analysis of artificial neural network models: Application in bankruptcy prediction

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Article ID: iaor200243
Country: Netherlands
Volume: 99
Issue: 1
Start Page Number: 403
End Page Number: 425
Publication Date: Dec 2000
Journal: Annals of Operations Research
Authors: , ,
Keywords: neural networks
Abstract:

This study compares the predictive performance of three neural network methods, namely the learning vector quantization, the radial basis function, and the feedforward network that uses the conjugate gradient optimization algorithm, with the performance of the logistic regression and the backpropagation algorithm. All these methods are applied to a dataset of 139 matched-pairs of bankrupt and non-bankrupt US firms for the period 1983–1994. The results of this study indicate that the contemporary neural network methods applied in the present study provide superior results to those obtained from the logistic regression method and the backpropagation algorithm.

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