D
2020
Machine learning forecasting of USA and PRC balance of trade in context of mutual sanctions
ROWLAND, Zuzana; Jaromír VRBKA and Marek VOCHOZKA
Basic information
Original name
Machine learning forecasting of USA and PRC balance of trade in context of mutual sanctions
Edition
73. vyd. Les Ulis, France, SHS Web of Conferences: Innovative Economic Symposium - Potential of Eurasian Economic Union (IES), p. nestránkováno, 16 pp. 2020
Other information
Type of outcome
Proceedings paper
Field of Study
50200 5.2 Economics and Business
Country of publisher
France
Confidentiality degree
is not subject to a state or trade secret
Publication form
printed version "print"
RIV identification code
RIV/75081431:_____/20:00002075
Organization unit
Institute of Technology and Business in České Budějovice
Keywords in English
forecasting; trade balance; machine learning; mutual sanctions; artificial neural networks
In the original language
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.
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