Time Series Forecasting Using Artificial Neural Network

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F15%3APU114719" target="_blank" >RIV/00216305:26510/15:PU114719 - 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
Time Series Forecasting Using Artificial Neural Network
Original language description
The paper aims to verify the ability of artificial neural networks to model and predict time series with seasonal and trend pattern. In this study the effectiveness of data preprocessing and time series analysis is examined, especially deseasonalizationand detrending as a basis for further neural network modelling and forecasting. In this paper it is proved that using deseasonalization as data preprocessing method, the best neural network performance is reached with respect to smallest Mean Squared Error showing the difference between outputs and targets. In general the research shows that prior data preprocessing enhances preciseness of further neural network prediction.
Czech name
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Czech description
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Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 25th International Business Information Management Association Conference
ISBN
978-0-9860419-4-5
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
527-535
Publisher name
International Business Information Management Association (IBIMA)
Place of publication
Amsterdam
Event location
Amsterdam
Event date
May 7, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000360508700049

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