Comparison of neural networks and regression time series in
estimating the development of the EU and the PRC trade balance

D 2019

Comparison of neural networks and regression time series in estimating the development of the EU and the PRC trade balance

VRBKA, Jaromír, Zuzana ROWLAND and Petr ŠULEŘ

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

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"

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

Abstract

ORIG CZ

V originále

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.

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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Citovat

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. Available from: https://dx.doi.org/10.1051/shsconf/20196101031.

@inproceedings{48601,
   author = {Vrbka, Jaromír and Rowland, Zuzana and Šuleř, Petr},
   address = {Les Ulis, France},
   booktitle = {SHS Web of Conferences: Innovative Economic Symposium 2018 - Milestones and Trends of World Economy (IES2018)},
   doi = {http://dx.doi.org/10.1051/shsconf/20196101031},
   editor = {Horák, J.},
   keywords = {trade balance; export and import; linear regression; neural networks},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Les Ulis, France},
   isbn = {978-2-7598-9063-7},
   pages = {nestránkováno},
   publisher = {EDP Sciences},
   title = {Comparison of neural networks and regression time series in estimating the development of the EU and the PRC trade balance},
   year = {2019}
}

TY  - JOUR
ID  - 48601
AU  - Vrbka, Jaromír - Rowland, Zuzana - Šuleř, Petr
PY  - 2019
TI  - Comparison of neural networks and regression time series in estimating the development of the EU and the PRC trade balance
PB  - EDP Sciences
CY  - Les Ulis, France
SN  - 9782759890637
KW  - trade balance
KW  - export and import
KW  - linear regression
KW  - neural networks
N2  - 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.
ER  -

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. \textit{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. Available from: https://dx.doi.org/10.1051/shsconf/20196101031.

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