Classification of companies with theassistance of self-learning neural networks

Vladimír Konečný, Oldřich Trenz and Eliška Svobodová
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Vladimír Konečný: Department of Computer Science, Faculty of Business and Economy, Mendel University in Brno, Brno, Czech Republic
Oldřich Trenz: Department of Computer Science, Faculty of Business and Economy, Mendel University in Brno, Brno, Czech Republic
Eliška Svobodová: Department of Regional and Business Economics, Faculty of Regional Development and International Studies, Mendel University in Brno, Brno, Czech Republic

Agricultural Economics, 2010, vol. 56, issue 2, 51-58

Abstract: The article is focused on rating classification of financial situation of enterprises using self-learning artificial neural networks. This is such a situation where the sets of objects of the particular classes are not well-known. Otherwise, it would be possible to use a multi-layer neural network with learning according to models. The advantage of a self-learning network is particularly the fact that its classification is not burdened by a subjective view. With reference to complexity, this sorting into groups may be very difficult even for experienced experts. The article also comprises the examples which confirm the described method functionality and the neural network model used. A major attention is focused on the classification of agricultural companies. For this purpose, financial indicators of eighty one agricultural companies were used.

Keywords: artificial intelligence; neural network; Kohonen network; learning; classification (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlage:v:56:y:2010:i:2:id:60-2009-agricecon

DOI: 10.17221/60/2009-AGRICECON

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