Use of neural networks for predicting development of USA export to China taking into account time series seasonality

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F19%3A00001684" target="_blank" >RIV/75081431:_____/19:00001684 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Use of neural networks for predicting development of USA export to China taking into account time series seasonality

Original language description

The objective of the contribution is to propose a methodology of taking into consideration the seasonal fluctuations in time series equalization using artificial neural networks on the example of the United States of America export to the People´s Republic of China. It resulted that all retained structures are applicable, but the retained MLP networks of the B alternative achieve better results. It has been proven that with the use of artificial neural networks, it is possible to predict the export development efficiency and with a high degree of accuracy, especially in the short term and considering specific seasonal fluctuations.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

50200 - Economics and Business

Project

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Continuities

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Ad Alta: Journal of interdisciplinary research

ISSN

1804-7890

e-ISSN

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Volume of the periodical

9

Issue of the periodical within the volume

2

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

6

Pages from-to

299-304

UT code for WoS article

000507312800053

EID of the result in the Scopus database

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