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Fuzzy, neuronet and discriminant models of diagnosing of possibility of enterprise's bankruptcy

A. Matviychuk

It is developed in the article the conceptual approach to modeling of financial stability of enterprises which permit to assess the state of the company through diagnosis of its bankruptcy possibility by finding similarities between the performance indicators of this company and enterprises have gone bankrupt and financially stable companies. The methods of theories of fuzzy logic, neural networks and discriminant analysis have been applied for the construction of economic and mathematical models of bankruptcy prediction. The analysis of car- ried out experiments revealed essential misfit of previously known discriminant models to conditions of transformational economy, and also shown relatively high correctness in predicting of enterprises’ bankruptcy with usage of developed by the author economic and mathematical models. All models are built on the same sets of explanatory variables and optimized on the same statistical data of Ukrainian enterprises. The testing of models also was carried out on one statistical sample, which allowed make a comparative analysis and obtain appropriate conclusions about the effectiveness of various mathematical tools to solve the problem of classification of objects of research.

Keywords. Enterprise’s financial stability, bankruptcy diagnostics, fuzzy logic, neural network, perceptron, self-organizing map, counter-propagation neural network, discriminant analysis.

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