VRBKA, Jaromír, Zuzana ROWLAND and Petr ŠULEŘ. Comparison of neural networks and regression time series in estimating the development of the EU and the PRC trade balance. In Horák, J.. SHS Web of Conferences: Innovative Economic Symposium 2018 - Milestones and Trends of World Economy (IES2018). Les Ulis, France: EDP Sciences, 2019. p. nestránkováno, 13 pp. ISBN 978-2-7598-9063-7. doi:10.1051/shsconf/20196101031.
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Basic information
Original name Comparison of neural networks and regression time series in estimating the development of the EU and the PRC trade balance
Name in Czech Porovnání neuronových sítí a regresních časových řad při odhadu vývoje obchodní bilance EU a ČLR
Authors VRBKA, Jaromír (203 Czech Republic, guarantor, belonging to the institution), Zuzana ROWLAND (203 Czech Republic, belonging to the institution) and Petr ŠULEŘ (203 Czech Republic, belonging to the institution).
Edition Les Ulis, France, SHS Web of Conferences: Innovative Economic Symposium 2018 - Milestones and Trends of World Economy (IES2018), p. nestránkováno, 13 pp. 2019.
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"
RIV identification code RIV/75081431:_____/19:00001516
Organization unit Institute of Technology and Business in České Budějovice
ISBN 978-2-7598-9063-7
Doi http://dx.doi.org/10.1051/shsconf/20196101031
UT WoS 000467727800031
Keywords (in Czech) obchodní bilance; export a import; lineární regrese; neuronové sítě
Keywords in English trade balance; export and import; linear regression; neural networks
Tags MAE, RIV19, WOS
Changed by Changed by: Mgr. Eva Hynešová, učo 23116. Changed: 7/6/2019 10:54.
Abstract
This paper aims to compare two useful methods, namely the accuracy of time series alignment through regression analysis and artificial neural networks, to assess the evolution of the EU and the People's Republic of China trade balance. The most appropriate curve is selected from the linear regression, and from the neural networks three useful neural structures are selected.
Abstract (in Czech)
Cílem tohoto příspěvku je porovnat dvě užitečné metody, a to přesnost vyrovnání časových řad pomocí regresní analýzy a umělých neuronových sítí, s cílem posoudit vývoj obchodní bilance EU a Čínské lidové republiky. Nejvhodnější křivka je vybrána z lineární regrese, z neuronových sítí jsou vybrány tři užitečné neuronové struktury.
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  • a concrete person Ing. Jaromír Vrbka, MBA, PhD., učo 10761
  • a concrete person Mgr. Eva Hynešová, učo 23116
  • a concrete person Mgr. Petr Šuleř, PhD., učo 24786
  • a concrete person Ing. Zuzana Rowland, MBA, PhD., učo 6614
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