ŠULEŘ, Petr, Zuzana ROWLAND and Tomáš KRULICKÝ. Evaluation of the accuracy of machine learning predictions of the Czech Republic´s exports to the China. Journal of Risk and Financial Management. Basel: MDPI, 2021, vol. 14, No 2, p. Nestránkováno, 28 pp. ISSN 1911-8066. Available from: https://dx.doi.org/10.3390/jrfm14020076. |
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@article{57322, author = {Šuleř, Petr and Rowland, Zuzana and Krulický, Tomáš}, article_location = {Basel}, article_number = {2}, doi = {http://dx.doi.org/10.3390/jrfm14020076}, keywords = {export; artificial neural networks; time series; future development; trade war}, language = {eng}, issn = {1911-8066}, journal = {Journal of Risk and Financial Management}, title = {Evaluation of the accuracy of machine learning predictions of the Czech Republic´s exports to the China}, url = {https://www.mdpi.com/1911-8074/14/2/76/htm}, volume = {14}, year = {2021} }
TY - JOUR ID - 57322 AU - Šuleř, Petr - Rowland, Zuzana - Krulický, Tomáš PY - 2021 TI - Evaluation of the accuracy of machine learning predictions of the Czech Republic´s exports to the China JF - Journal of Risk and Financial Management VL - 14 IS - 2 SP - Nestránkováno EP - Nestránkováno PB - MDPI SN - 19118066 KW - export KW - artificial neural networks KW - time series KW - future development KW - trade war UR - https://www.mdpi.com/1911-8074/14/2/76/htm N2 - The objective of this contribution is to predict the development of the Czech Republic's exports to the China using artificial neural networks (ANN). For the purpose specified, three experiments are carried out, the results of which are described in detail. For the first, second and third experiments, ANN for predicting the development of exports are generated on the basis of a time series with a 1-month, 5-month and 10-month time delay, respectively. ER -
ŠULEŘ, Petr, Zuzana ROWLAND and Tomáš KRULICKÝ. Evaluation of the accuracy of machine learning predictions of the Czech Republic´s exports to the China. \textit{Journal of Risk and Financial Management}. Basel: MDPI, 2021, vol.~14, No~2, p.~Nestránkováno, 28 pp. ISSN~1911-8066. Available from: https://dx.doi.org/10.3390/jrfm14020076.
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