Comparison of time series forecasting with artificial neural network and statistical approach
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F11%3APU94839" target="_blank" >RIV/00216305:26210/11:PU94839 - isvavai.cz</a>
Alternative codes found
RIV/62156489:43110/11:00169780
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Comparison of time series forecasting with artificial neural network and statistical approach
Original language description
The experiment described in this paper consists of a comparison of results computed by Multi-layer perceptron network with different learning algorithms previously published and results computed with different types of ARMA models. For the network configuration an analytical approach has been applied through the cross-validation method. We performed an exact comparison of both approaches on real-world data set. Results of two types of artificial neural network learning algorithms are compared with two algorithms of statistical prediction of future values.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis
ISSN
1211-8516
e-ISSN
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Volume of the periodical
2011
Issue of the periodical within the volume
2
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
6
Pages from-to
347-352
UT code for WoS article
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EID of the result in the Scopus database
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