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Learning Bayesian Network to Predict Group Emotion in Kindergarten by Evolutionary Computation Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Bioclimatic House Heat Exchanger Behavior Prediction with Time Series Modeling

Authors : Bruno Baruque, Esteban Jove, José Luis Casteleiro-Roca, Santiago Porras, José Luis Calvo-Rolle, Emilio Corchado

Published in: International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding

Publisher: Springer International Publishing

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Abstract

The Heat Pump with geothermal exchanger is one of the best methods to heat up a building. The heat exchanger is one of the most representative elements when a heat pump is employed as building heating system. In the present study, a novel intelligent system was designed to predict the performance of on this kind of heating equipment. The novel approach has been successfully empirically tested under a real dataset obtained during measurements along one year. It was based on time series modeling. Then, the model was validated and verified; it obtains good results in all the operating conditions ranges.

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previous chapter Gas Consumption Prediction Based on Artificial Neural Networks for Residential Sectors
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Metadata
Title
Bioclimatic House Heat Exchanger Behavior Prediction with Time Series Modeling
Authors
Bruno Baruque
Esteban Jove
José Luis Casteleiro-Roca
Santiago Porras
José Luis Calvo-Rolle
Emilio Corchado
Copyright Year
2018
Book
International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding

Print ISBN: 978-3-319-67179-6

Electronic ISBN: 978-3-319-67180-2

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-67180-2_11

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