Classification of companies with assistance of self-learning neural networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F10%3A00144585" target="_blank" >RIV/62156489:43110/10:00144585 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Classification of companies with assistance of self-learning neural networks

Popis výsledku v původním jazyce

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 possibleto 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 groupsmay 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.

Název v anglickém jazyce

Classification of companies with assistance of self-learning neural networks

Popis výsledku anglicky

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 possibleto 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 groupsmay 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.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2010

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Agricultural economics : Zemědělská ekonomika

ISSN

0139-570X

e-ISSN

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Svazek periodika

56

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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