J 2020

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

VRBKA, Jaromír; Petr ŠULEŘ; Veronika MACHOVÁ and Jakub HORÁK

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

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

References:

URL

RIV identification code

RIV/75081431:_____/20:00002107

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: 30/6/2021 13:41, Mgr. Nikola Petříková

Abstract

V originále

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.
Displayed: 30/6/2025 23:33