Classification of companies with the assistance of self-learning neural networks

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 w...

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Bibliographic Details
Published in:Agricultural economics (Praha) 2010-02, Vol.56 (2)
Main Authors: Konecny, V.,Mendelova Zemedelska a Lesnicka Univ., Brno (Czech Republic). Ustav Informatiky, Trenz, O.,Mendelova Zemedelska a Lesnicka Univ., Brno (Czech Republic). Ustav Informatiky, Svobodova, E.,Mendelova Zemedelska a Lesnicka Univ., Brno (Czech Republic). Ustav Regionalni a Podnikove Ekonomiky
Format: Article
Language:English
Subjects:
AGRICULTURAL SECTOR
APPRENTISSAGE
APRENDIZAJE
ARTIFICIAL INTELLIGENCE
CLASIFICACION
CLASSIFICATION
COMPUTER SOFTWARE
EMPRESAS
ENTERPRISES
ENTREPRISE
EXPLOITATION AGRICOLE
EXPLOTACIONES AGRARIAS
FARMS
FINANCIAL SITUATION
http://www.fao.org/aos/agrovoc#c_10626
http://www.fao.org/aos/agrovoc#c_1653
http://www.fao.org/aos/agrovoc#c_24008
http://www.fao.org/aos/agrovoc#c_27064
http://www.fao.org/aos/agrovoc#c_2801
http://www.fao.org/aos/agrovoc#c_2809
http://www.fao.org/aos/agrovoc#c_35369
http://www.fao.org/aos/agrovoc#c_37467
http://www.fao.org/aos/agrovoc#c_37978
INTELIGENCIA ARTIFICIAL
INTELLIGENCE ARTIFICIELLE
LEARNING
LOGICIEL
NEURAL NETWORKS
PROGRAMAS DE ORDENADOR
REDES DE NEURONAS
RESEAU DE NEURONES
SECTEUR AGRICOLE
SECTOR AGRARIO
SITUACION FINANCIERA
SITUATION FINANCIERE
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Summary: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 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.
ISSN:0139-570X