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

Authors

ROWLAND, Zuzana (203 Czech Republic, guarantor, belonging to the institution), Jaromír VRBKA (203 Czech Republic, belonging to the institution) and Marek VOCHOZKA (203 Czech Republic, belonging to the institution)

Edition

73. vyd. Les Ulis, France, SHS Web of Conferences: Innovative Economic Symposium - Potential of Eurasian Economic Union (IES), p. nestránkováno, 16 pp. 2020

Publisher

EDP Sciences

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

50200 5.2 Economics and Business

Country of publisher

France

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

RIV identification code

RIV/75081431:_____/20:00002075

Organization unit

Institute of Technology and Business in České Budějovice

ISBN

978-2-7598-9094-1

UT WoS

000648964700025

Keywords in English

forecasting; trade balance; machine learning; mutual sanctions; artificial neural networks

Tags

BPE_MAE, RIV21, WOS
Změněno: 16/6/2021 08:20, Mgr. Nikola Petříková

Abstract

V originále

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.
Displayed: 4/11/2024 22:02