Electricity Forecasting by Using Self-Organizing Maps (SOM) and Feed-Forward Neural Network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F12%3A43916362" target="_blank" >RIV/49777513:23220/12:43916362 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Electricity Forecasting by Using Self-Organizing Maps (SOM) and Feed-Forward Neural Network
Original language description
This paper shows approaches forelectricity price forecasting. The hybrid fundamental model by using Self-organizing Maps (SOM) and FEED-forward neural network is shown. Separation of whole input data set to smaller groups is presented and proposal for elimination of systematic errorson the output of the model is suggested. Comparison with already existed models and other approaches for prediction of electricity prices are mentioned and carried out in this article. As evidence of model confidence the comparison with real market electricity price iscalculated.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
JE - Non-nuclear power engineering, energy consumption and utilization
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Electric Power Engineering and Ecology - Selected Parts IV.
ISBN
978-80-7300-461-3
Number of pages of the result
12
Pages from-to
62-74
Number of pages of the book
94
Publisher name
BEN - technická literatura
Place of publication
Praha
UT code for WoS chapter
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