Neuro-fuzzy modeling in bankruptcy prediction

Neuro-fuzzy modeling in bankruptcy prediction

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Article ID: iaor20041426
Country: Serbia
Volume: 13
Issue: 2
Start Page Number: 165
End Page Number: 174
Publication Date: Jul 2003
Journal: Yugoslav Journal of Operations Research
Authors: ,
Keywords: fuzzy sets
Abstract:

For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm), combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can simulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.

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