Artificial neural networks in artificial time series prediction benchmark
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F11%3A43865533" target="_blank" >RIV/70883521:28140/11:43865533 - isvavai.cz</a>
Alternative codes found
RIV/70883521:28110/11:43865533
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Artificial neural networks in artificial time series prediction benchmark
Original language description
The work is aimed to research of predicting abilities of artificial neural networks. The characteristic samples of artificial neural network types were selected to be compared in numerous simulations, while influences of key parameters are studied. The tested artificial networks are as follows: multilayered feed-forward neural network, recurrent Elman neural network, adaptive linear network and radial basis function neural network.
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
JP - Industrial processes and processing
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
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
International Journal of Mathematical Models and Methods in Applied Science
ISSN
1998-0140
e-ISSN
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Volume of the periodical
5
Issue of the periodical within the volume
6
Country of publishing house
GB - UNITED KINGDOM
Number of pages
9
Pages from-to
1085-1093
UT code for WoS article
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EID of the result in the Scopus database
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