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Upgrade of an artificial neural network prediction method for electrical consumption forecasting using an hourly temperature curve model

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Upgrade of an artificial neural network prediction method for electrical consumption forecasting using an hourly temperature curve model

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Roldán Blay, C.; Escrivá-Escrivá, G.; Álvarez Bel, CM.; Roldán Porta, C.; Rodriguez-Garcia, J. (2013). Upgrade of an artificial neural network prediction method for electrical consumption forecasting using an hourly temperature curve model. Energy and Buildings. 60:38-46. doi:10.1016/j.enbuild.2012.12.009

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/45164

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Título: Upgrade of an artificial neural network prediction method for electrical consumption forecasting using an hourly temperature curve model
Autor:
Entidad UPV: Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica
Universitat Politècnica de València. Instituto de Ingeniería Energética - Institut d'Enginyeria Energètica
Fecha difusión:
Resumen:
This paper presents the upgrading of a method for predicting short-term building energy consumption that was previously developed by the authors (EUs method). The upgrade uses a time temperature curve (TTC) forecast model. ...[+]
Palabras clave: Temperature curve model , Building energy consumption forecast , Artificial neural networks , Building end-uses
Derechos de uso: Reserva de todos los derechos
Fuente:
Energy and Buildings. (issn: 0378-7788 )
DOI: 10.1016/j.enbuild.2012.12.009
Editorial:
Elsevier
Versión del editor: http://dx.doi.org/10.1016/j.enbuild.2012.12.009
Agradecimientos:
This research work has been possible with the support of the Universitat Politecnica de Valencia (Spain) with grant #CE 19990032.
Tipo: Artículo

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