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Description
  • The article is focused on rating classification of financial situation of enterprises using self-learning artificial neural networks. This is such a situation where sets of objects of 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 neural network model used. Major attention is focused on classification of agricultural companies. For this purpose financial indicators of eighty-one agricultural companies were used.
  • The article is focused on rating classification of financial situation of enterprises using self-learning artificial neural networks. This is such a situation where sets of objects of 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 neural network model used. Major attention is focused on classification of agricultural companies. For this purpose financial indicators of eighty-one agricultural companies were used. (en)
Title
  • Classification of companies with assistance of self-learning neural networks
  • Classification of companies with assistance of self-learning neural networks (en)
skos:prefLabel
  • Classification of companies with assistance of self-learning neural networks
  • Classification of companies with assistance of self-learning neural networks (en)
skos:notation
  • RIV/62156489:43110/10:00144585!RIV10-MSM-43110___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM6215648904)
http://linked.open...iv/cisloPeriodika
  • 2
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 250905
http://linked.open...ai/riv/idVysledku
  • RIV/62156489:43110/10:00144585
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • classification; learning; Kohonen network; artificial intelligence; neural network (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • CZ - Česká republika
http://linked.open...ontrolniKodProRIV
  • [E2F1122D336B]
http://linked.open...i/riv/nazevZdroje
  • Agricultural economics : Zemědělská ekonomika
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 56
http://linked.open...iv/tvurceVysledku
  • Konečný, Vladimír
  • Trenz, Oldřich
  • Svobodová, Eliška
http://linked.open...n/vavai/riv/zamer
issn
  • 0139-570X
number of pages
http://localhost/t...ganizacniJednotka
  • 43110
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