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

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

50200 - Economics and Business

Projekt

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Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název periodika

Ad Alta: Journal of interdisciplinary research

ISSN

1804-7890

e-ISSN

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Svazek periodika

9

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

6

Strana od-do

299-304

Kód UT WoS článku

000507312800053

EID výsledku v databázi Scopus

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