C 2023

Methodology

HORÁK, Jakub, Veronika MACHOVÁ, Tomáš KRULICKÝ and Valentina VYCHESLAVOVNA MANTULENKO

Basic information

Original name

Methodology

Authors

HORÁK, Jakub (203 Czech Republic, guarantor, belonging to the institution), Veronika MACHOVÁ (203 Czech Republic, belonging to the institution), Tomáš KRULICKÝ (203 Czech Republic, belonging to the institution) and Valentina VYCHESLAVOVNA MANTULENKO

Edition

Neuveden, Development of World Trade in the Context of the COVID-19 Pandemic, p. 61-65, 5 pp. 2023

Publisher

Springer Science and Business Media Deutschland GmbH

Other information

Language

English

Type of outcome

Kapitola resp. kapitoly v odborné knize

Field of Study

50200 5.2 Economics and Business

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

Organization unit

Institute of Technology and Business in České Budějovice

ISBN

978-3-031-27259-2

Keywords in English

Economic crisis; Financial crisis; Covid-19; Energy; Food industry; World economy; Globalization; National markets; Export Import; Global trade; Russia; Czech Republic; Pandemic; Resources; Balance of trade; Engineering; Automotive industry
Změněno: 21/7/2023 13:41, Barbora Kroupová

Abstract

V originále

Abstract The chapter that focuses on methodology describes the structure of the data that provide a background for the research. Specifically, these are monthly data concerning the volume of export, import, and balance of trade between Russia and the Czech Republic for a specific period, or more precisely, for more than 27 years. In addition to the specification of the data set, this chapter also describes the methods used and the process based on which the results are obtained. As the main tool, the method of artificial neural networks is used, specifically, the multilayer perceptron (MLP) as one of the most commonly used networks in practice, and one of the latest models of neural networks, a three-layer feedforward neural network RBF.