Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balance
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F75081431%3A_____%2F19%3A00001519" target="_blank" >RIV/75081431:_____/19:00001519 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1051/shsconf/20196101023" target="_blank" >http://dx.doi.org/10.1051/shsconf/20196101023</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1051/shsconf/20196101023" target="_blank" >10.1051/shsconf/20196101023</a>
Alternative languages
Result language
angličtina
Original language name
Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balance
Original language description
The aim of this paper is to compare the accuracy of time series alignment by means of regression analysis and neural networks on the example of the trade balance of the Czech Republic and the People's Republic of China. This is a monthly balance starting in 2000 and ending in July 2018.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
50204 - Business and management
Result continuities
Project
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Continuities
N - Vyzkumna aktivita podporovana z neverejnych zdroju
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
SHS Web of Conferences: Innovative Economic Symposium 2018 - Milestones and Trends of World Economy (IES2018)
ISBN
9782759890637
ISSN
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e-ISSN
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Number of pages
13
Pages from-to
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Publisher name
EDP Sciences
Place of publication
Les Ulis, France
Event location
Beijing, PR China
Event date
Nov 8, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000467727800023