Improving the neural network mathematical model of corporate bankruptcy

This paper continues research on the development of Neural Network Models (NNM) for predicting and diagnosing bankruptcy of enterprises, various aspects of which were discussed in [1– 2]. From the point of view of techniques, the task of improving accuracy, adequacy and quality of NNM in conditions of incompleteness, inaccuracy, and uncertainty of data is of continuing research interest.