SHS Web Conf.
Volume 73, 2020Innovative Economic Symposium 2019 – Potential of Eurasian Economic Union (IES2019)
|Number of page(s)||16|
|Section||Potential of the Eurasian Economic Union|
|Published online||13 January 2020|
Machine learning forecasting of USA and PRC balance of trade in context of mutual sanctions
Institute of Technology and Business, School of Expertness and Valuation, Okružní 517/10, 37001 české Budějovice Czech Republic
* Corresponding author: email@example.com
The USA decided to regulate the trade more by imposing tariffs on specific types of traded goods. It is therefore more interesting to find out whether the current technologies based on artificial intelligence with time series influenced by extraordinary factors such as the trade war between two powers are able to work. The objective of the contribution 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. Mutual sanctions of both states did not affect the result of machine learning forecasting.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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