Hybrid RBF + GA Neural Network for Electricity Load Forecast

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F12%3A%230004396" target="_blank" >RIV/47813059:19240/12:#0004396 - 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
Hybrid RBF + GA Neural Network for Electricity Load Forecast
Original language description
The paper evaluate RBF neural network as a method of artificial intelligence for half-hourly electricity demand prediction. Using Australian data we show that Hybrid RBF + GA neural network outperform RBF neural network and number of baselines. We also analyze that hybrid RBF + GA model can achieved lower MAPE than RBF neural network alone.
Czech name
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Czech description
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Project
<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
18th International Conference on Soft Computing - MENDEL 2012
ISBN
978-80-214-4540-6
ISSN
1803-3814
e-ISSN
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Number of pages
6
Pages from-to
280-285
Publisher name
VUT Brno
Place of publication
Brno
Event location
Brno, ČR
Event date
Jan 1, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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