VRBKA, Jaromír, Petr ŠULEŘ, Veronika MACHOVÁ and Jakub HORÁK. Evaluation of performance of MLP neural networks and RBF neural networks in adjusting time series of the development of the trade balance between the USA and the PRC. Littera Scripta. České Budějovice, Česká republika: Vysoká škola technická a ekonomická, 2020, vol. 13, No 2, p. 23-38. ISSN 1805-9112.
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Basic information
Original name Evaluation of performance of MLP neural networks and RBF neural networks in adjusting time series of the development of the trade balance between the USA and the PRC
Authors VRBKA, Jaromír (203 Czech Republic, guarantor, belonging to the institution), Petr ŠULEŘ (203 Czech Republic, belonging to the institution), Veronika MACHOVÁ (203 Czech Republic, belonging to the institution) and Jakub HORÁK (203 Czech Republic, belonging to the institution).
Edition Littera Scripta, České Budějovice, Česká republika, Vysoká škola technická a ekonomická, 2020, 1805-9112.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 50200 5.2 Economics and Business
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
WWW URL
Organization unit Institute of Technology and Business in České Budějovice
Keywords in English multilayer neural networks; RBF; trade balance; future development prediction; USA; People's Republic of China; correlation coefficient
Tags BPE_MAE, RIV21
Changed by Changed by: Mgr. Nikola Vyhlidalová, učo 28324. Changed: 30/6/2021 13:41.
Abstract
Authors aim is to analyse and evaluate the performance of multilayer neural networks and neural networks of radial basis function in adjusting time series on the example of the trade balance between the United States and the People's Republic of China.
PrintDisplayed: 17/10/2021 14:08