Bankruptcy or success? The effective prediction of a company's financial development using LSTM
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F20%3A00001825" target="_blank" >RIV/75081431:_____/20:00001825 - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/record/display.uri?eid=2-s2.0-85091137788&origin=resultslist&sort=plf-f&src=s&st1=Bankruptcy+or+success%3f+The+effective+prediction+of+a+company%27s+financial+development+using+LSTM&st2=&sid=ae2d7679e9af4b3898dc19e0e6b0128f&sot=b&s" target="_blank" >https://www.scopus.com/record/display.uri?eid=2-s2.0-85091137788&origin=resultslist&sort=plf-f&src=s&st1=Bankruptcy+or+success%3f+The+effective+prediction+of+a+company%27s+financial+development+using+LSTM&st2=&sid=ae2d7679e9af4b3898dc19e0e6b0128f&sot=b&s</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/su12187529" target="_blank" >10.3390/su12187529</a>
Alternative languages
Result language
angličtina
Original language name
Bankruptcy or success? The effective prediction of a company's financial development using LSTM
Original language description
The objective of this contribution is to create a methodology for the identification of a company failure (bankruptcy) using artificial neural networks with at least one long short-term memory (LSTM) layer. A bankruptcy model was created using deep learning, for which at least one layer of LSTM was used for the construction of the NN. For the purposes of this contribution, Wolfram's Mathematica 13.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
50200 - Economics and Business
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Sustainability
ISSN
2071-1050
e-ISSN
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Volume of the periodical
12
Issue of the periodical within the volume
18
Country of publishing house
CH - SWITZERLAND
Number of pages
18
Pages from-to
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UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85091137788