Neuro-discriminate Model for the Forecasting of Changes of Companies Financial Standings on the Basis of Self-organizing Maps

Authors:
Egidijus Merkevičius;Gintautas Garšva;Rimvydas Simutis
Affiliations:
Department of Informatics, Kaunas Faculty of Humanities, Vilnius University, Muitinės st. 8, LT- 44280 Kaunas, Lithuania;Department of Informatics, Kaunas Faculty of Humanities, Vilnius University, Muitinės st. 8, LT- 44280 Kaunas, Lithuania and Department of Information Systems, Kaunas University of Technology ...;Department of Informatics, Kaunas Faculty of Humanities, Vilnius University, Muitinės st. 8, LT- 44280 Kaunas, Lithuania
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
Year:
2007

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Abstract

This article presents the way how creditor can predict the trends of debtors financial standing. We propose the model for forecasting changes of financial standings. Model is based on the Self-organizing maps as a tool for prediction, grouping and visualization of large amount of data. Inputs for training of SOM are financial ratios calculated according any discriminate bankruptcy model. Supervised neural network lets automatically increase accuracy of performance via changing of weights of ratios.