Equalizing seasonal time series using artificial neural networks in predicting the Euro-Yuan exchange rate

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F19%3A00001559" target="_blank" >RIV/75081431:_____/19:00001559 - isvavai.cz</a>
Výsledek na webu
<a href="http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=18&SID=F6xnU9HOLRR1jfSCtjp&page=1&doc=1" target="_blank" >http://apps.webofknowledge.com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=18&SID=F6xnU9HOLRR1jfSCtjp&page=1&doc=1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/jrfm12020076" target="_blank" >10.3390/jrfm12020076</a>

Jazyk výsledku
angličtina
Název v původním jazyce
Equalizing seasonal time series using artificial neural networks in predicting the Euro-Yuan exchange rate
Popis výsledku v původním jazyce
This contribution aims to propose a methodology for considering seasonal fluctuations in equalizing time series by means of artificial neural networks on the example of Euro and Chinese Yuan. Regression by means of neural networks is carried out. There are two network sets generated, of which the second one focuses on the seasonal fluctuations.
Název v anglickém jazyce
Equalizing seasonal time series using artificial neural networks in predicting the Euro-Yuan exchange rate
Popis výsledku anglicky
This contribution aims to propose a methodology for considering seasonal fluctuations in equalizing time series by means of artificial neural networks on the example of Euro and Chinese Yuan. Regression by means of neural networks is carried out. There are two network sets generated, of which the second one focuses on the seasonal fluctuations.

Rok uplatnění
2019
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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