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@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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