Forecasting Weekly Electric Load Using a Hybrid Fuzzy-Neural Network Approach
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F01%3APU24984" target="_blank" >RIV/00216305:26220/01:PU24984 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26210/01:PU23845
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Forecasting Weekly Electric Load Using a Hybrid Fuzzy-Neural Network Approach
Original language description
Weekly forecasting for Czech electric power utility using artificial neural network. The networks were trained with actual and historical data and a comparison and evaluation were performed.
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
JA - Electronics and optoelectronics
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
2001
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Inženýrská mechanika - Engineering Mechanics
ISSN
1210-2717
e-ISSN
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Volume of the periodical
2001
Issue of the periodical within the volume
11-12
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
6
Pages from-to
24-29
UT code for WoS article
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EID of the result in the Scopus database
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