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One-Day Building Cooling Load Prediction Based on Bidirectional Recurrent Neural Network

Xia, Ye

Abstract Short-term building cooling load prediction is very important for building energy management tasks. Traditional way relies on physical principles. Due to the nonlinearity of the features of the data, it is a challenge for prediction. This work applies the Bidirectional Recurrent Neural Network (BRNNs) in prediction of 24-h ahead building cooling load profiles. The results show that BRNNs have good performance in prediction on building cooling load prediction. The mode can predict the building cooling load profiles effectively.

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One-Day Building Cooling Load Prediction Based on Bidirectional Recurrent Neural Network

Xia, Ye

Abstract Short-term building cooling load prediction is very important for building energy management tasks. Traditional way relies on physical principles. Due to the nonlinearity of the features of the data, it is a challenge for prediction. This work applies the Bidirectional Recurrent Neural Network (BRNNs) in prediction of 24-h ahead building cooling load profiles. The results show that BRNNs have good performance in prediction on building cooling load prediction. The mode can predict the building cooling load profiles effectively.

One-Day Building Cooling Load Prediction Based on Bidirectional Recurrent Neural Network

Xia, Ye

Abstract Short-term building cooling load prediction is very important for building energy management tasks. Traditional way relies on physical principles. Due to the nonlinearity of the features of the data, it is a challenge for prediction. This work applies the Bidirectional Recurrent Neural Network (BRNNs) in prediction of 24-h ahead building cooling load profiles. The results show that BRNNs have good performance in prediction on building cooling load prediction. The mode can predict the building cooling load profiles effectively.

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Title:

One-Day Building Cooling Load Prediction Based on Bidirectional Recurrent Neural Network

Contributors:

Xia, Ye (author)

Published in:

Proceedings of the Fifth Euro-China Conference on Intelligent Data Analysis and Applications ; 551-557

Advances in Intelligent Systems and Computing ; 891

Publication date:

2018-12-25

Size:

7 pages

ISBN:

978-3-030-03765-9 , 978-3-030-03766-6

ISSN:

2194-5357 , 2194-5365

DOI:

https://doi.org/10.1007/978-3-030-03766-6_62

Type of media:

Article/Chapter (Book)

Type of material:

Electronic Resource

Language:

English

Keywords:

Building cooling load , Short-term prediction , BRNNs Engineering , Computational Intelligence , Artificial Intelligence

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