Machine learning forecasting of USA and PRC balance of trade in context of mutual sanctions

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F20%3A00002075" target="_blank" >RIV/75081431:_____/20:00002075 - isvavai.cz</a>
Result on the web
<a href="https://www.shs-conferences.org/articles/shsconf/pdf/2020/01/shsconf_ies_2019_01025.pdf" target="_blank" >https://www.shs-conferences.org/articles/shsconf/pdf/2020/01/shsconf_ies_2019_01025.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Machine learning forecasting of USA and PRC balance of trade in context of mutual sanctions
Original language description
Authors aim is to examine and subsequently equalize two time series –the USA import from the PRC and the USA export to the PRC. The dataset shows the course of the time series at monthly intervals between January 2000 and July 2019. 10,000 multilayer perceptron networks (MLP) are generated, out of which 5 with the best characteristics are retained. It has been proved that multilayer perceptron networks are a suitable tool for forecasting the development of the time series if there are no sudden fluctuations.
Czech name
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Czech description
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Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
SHS Web of Conferences: Innovative Economic Symposium - Potential of Eurasian Economic Union (IES)
ISBN
9782759890941
ISSN
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e-ISSN
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Number of pages
16
Pages from-to
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Publisher name
EDP Sciences
Place of publication
Les Ulis, France
Event location
České Budějovice, Česká republika
Event date
Nov 7, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000648964700025

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