Machine learning methods to forecast temperature in buildings
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Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
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Título
Machine learning methods to forecast temperature in buildingsAutoría
Fecha de publicación
2013Editor
ElsevierISSN
0957-4174Cita bibliográfica
Expert Systems with Applications Volume 40, Issue 4, March 2013, Pages 1061–1068Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S0957417412009918Palabras clave / Materias
Resumen
Efficient management of energy in buildings saves a very important amount of resources (both economic and technological). As a consequence, there is a very active research in this field. One of the keys of energy ... [+]
Efficient management of energy in buildings saves a very important amount of resources (both economic and technological). As a consequence, there is a very active research in this field. One of the keys of energy management is the prediction of the variables that directly affect building energy consumption and personal comfort. Among these variables, one can highlight the temperature in each room of a building. In this work we apply different machine learning techniques along with other classical ones for predicting the temperatures in different rooms. The obtained results demonstrate the validity of these techniques for predicting temperatures and, therefore, for the establishment of optimal policies of energy consumption. [-]
Publicado en
Expert Systems with Applications, 2013, vol. 40, no 4Derechos de acceso
Copyright © 2012 Elsevier Ltd. All rights reserved.
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