VRBKA, Jaromír and Marek VOCHOZKA. Considering seasonal fluctuations on balancing time series with the use of artificial neural networks when forecasting US imports from the PRC. In Horák, J., Vrbka, J., Rowland, Z. SHS Web of Conferences: Innovative Economic Symposium - Potential of Eurasian Economic Union (IES). 73rd ed. Les Ulis, France: EDP Sciences. p. nestránkováno, 12 pp. ISBN 978-2-7598-9094-1. 2020.
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Basic information
Original name Considering seasonal fluctuations on balancing time series with the use of artificial neural networks when forecasting US imports from the PRC
Authors VRBKA, Jaromír (203 Czech Republic, guarantor, 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, 12 pp. 2020.
Publisher EDP Sciences
Other information
Original language English
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"
WWW URL
RIV identification code RIV/75081431:_____/20:00002078
Organization unit Institute of Technology and Business in České Budějovice
ISBN 978-2-7598-9094-1
UT WoS 000648964700033
Keywords in English forecasting models; artificial neural networks; time series; development
Tags BPE_MAE, RIV21, WOS
Changed by Changed by: Mgr. Nikola Petříková, učo 28324. Changed: 16/6/2021 10:13.
Abstract
Authors aim is to propose a particular methodology to be used to regard seasonal fluctuations on balancing time series while using artificial neural networks based on the example ofimports from the People's Republic of China (PRC) to the USA(US). The difficulty of forecasting the volume of foreign trade is usually given by the limitations of many conventional forecasting models. For the improvement of forecasting it is necessary topropose an approach that would hybridize econometric models and artificial intelligence models.
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