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Feature selection for interval forecasting of electricity demand time series data
conference contribution
posted on 2023-01-27, 04:38 authored by M Rana, I Koprinska, Abbas KhosraviAbbas KhosraviFeature selection for interval forecasting of electricity demand time series data
History
Pagination
445-462Location
GERMANY, HamburgPublisher DOI
Start date
2014-09-15End date
2014-09-19ISSN
2193-9349eISSN
2193-9357ISBN-13
9783319099026Language
EnglishPublication classification
E1.1 Full written paper - refereedEditor/Contributor(s)
KoprinkovaHristova P, Mladenov V, Kasabov NKTitle of proceedings
Artificial Neural Networks - Methods and Applications in Bio-/NeuroinformaticsEvent
International Conference on Artificial Neural Networks (ICANN)Publisher
SPRINGER-VERLAG BERLINUsage metrics
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No categories selectedKeywords
Science & TechnologyTechnologyComputer Science, Information SystemsComputer Science, Interdisciplinary ApplicationsComputer Science, Theory & MethodsComputer ScienceElectricity demand forecastingprediction intervalsuncertainty quantificationneural networksfeature selectionmutual informationcorrelation
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