VOCHOZKA, Marek and Zuzana ROWLAND. Forecasting trade balance of Czech Republic and People´s Republic of China in equalizing time series and considering seasonal fluctuations. 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, 2020, p. nestránkováno, 14 pp. ISBN 978-2-7598-9094-1.
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Basic information
Original name Forecasting trade balance of Czech Republic and People´s Republic of China in equalizing time series and considering seasonal fluctuations
Authors VOCHOZKA, Marek (203 Czech Republic, guarantor, belonging to the institution) and Zuzana ROWLAND (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, 14 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:_____/20:00002070
Organization unit Institute of Technology and Business in České Budějovice
ISBN 978-2-7598-9094-1
UT WoS 000648964700032
Keywords in English trade balance; Czech Republic; People´s Republic of China; time series; seasonal fluctuations
Tags BPE_MAE, RIV21, WOS
Changed by Changed by: Mgr. Nikola Petříková, učo 28324. Changed: 15/6/2021 09:34.
Abstract
Authors aim is to introduce a methodology for considering seasonal fluctuations in equalizing time series using artificial neural networks on the example of the Czech Republic and the People ́s Republic of China trade balance. The data available is the data on monthly balance for the period between January 2000 and July 2018, that is, 223 input data. The unit is Euro. The data for the analysis are available on the World Bank web pages etc. Regression analysis is carried out using artificial neural networks.
PrintDisplayed: 7/6/2024 07:41