D 2020

Considering seasonal fluctuations on balancing time series with the use of artificial neural networks when forecasting US imports from the PRC

VRBKA, Jaromír and Marek VOCHOZKA

Basic information

Original name

Considering seasonal fluctuations on balancing time series with the use of artificial neural networks when forecasting US imports from the PRC

Authors

VRBKA, Jaromír (203 Czech Republic, guarantor, belonging to the institution) and Marek VOCHOZKA (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, 12 pp. 2020

Publisher

EDP Sciences

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

50200 5.2 Economics and Business

Country of publisher

France

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

RIV identification code

RIV/75081431:_____/20:00002078

Organization unit

Institute of Technology and Business in České Budějovice

ISBN

978-2-7598-9094-1

UT WoS

000648964700033

Keywords in English

forecasting models; artificial neural networks; time series; development

Tags

BPE_MAE, RIV21, WOS
Změněno: 16/6/2021 10:13, Mgr. Nikola Petříková

Abstract

V originále

Authors aim is to propose a particular methodology to be used to regard seasonal fluctuations on balancing time series while using artificial neural networks based on the example ofimports from the People's Republic of China (PRC) to the USA(US). The difficulty of forecasting the volume of foreign trade is usually given by the limitations of many conventional forecasting models. For the improvement of forecasting it is necessary topropose an approach that would hybridize econometric models and artificial intelligence models.
Displayed: 29/12/2024 18:37