Wrapper Feature Selection Significantly Improves Nonlinear Prediction of Electricity Spot Prices
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00208779" target="_blank" >RIV/68407700:21230/13:00208779 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/SMC.2013.203" target="_blank" >http://dx.doi.org/10.1109/SMC.2013.203</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SMC.2013.203" target="_blank" >10.1109/SMC.2013.203</a>
Alternative languages
Result language
angličtina
Original language name
Wrapper Feature Selection Significantly Improves Nonlinear Prediction of Electricity Spot Prices
Original language description
The paper describes the selection of input delays for Focused Time Delay Neural Network (FTDNN). The problem is understood as a feature subset selection problem, where one looks for a set of features (input delays) that minimizes the mean absolute percentage error. This combinatorial optimization problem is solved using sequential forward search. First, an application of the prediction method to hourly Ontario electricity price forecasting is presented, demonstrating the importance of the feature selection. Although the network with only one hidden unit was used, the wrapper based feature selection caused that it outperforms all state-of the art approaches considered for comparison.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GP13-21696P" target="_blank" >GP13-21696P: Feature selection for temporal context aware models of multivariate time series</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings 2013 IEEE International Conference on Systems, Man, and Cybernetics
ISBN
978-0-7695-5154-8
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
1171-1174
Publisher name
IEEE
Place of publication
Piscataway
Event location
Manchester
Event date
Oct 13, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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