Building Energy Use Intensity Prediction with Artificial Neural Networks
Ładowanie...
Data
2023
Tytuł czasopisma
ISSN czasopisma
Tytuł tomu
Wydawca
Wydawnictwo Politechniki Łódzkiej
Lodz University of Technology Press
Lodz University of Technology Press
Abstrakt
In this paper the authors propose the construction and examine
the performance of the artificial neural network for energy use intensity prediction
for residential buildings. The network’s type is the standard multilayer
perceptron and its training dataset contains the data of 768 residential
buildings where the training pattern for an individual building consists of
8 parameters describing the building’s geometry along with its lighting and
glazing conditions while the only output value is the building’s actual energy
use intensity characteristics. Experimental study shows that the mean absolute
percentage error of prediction of the energy use intensity evaluated for
buildings data present in the network’s test set does not exceed 1.8%, what
might be considered a highly satisfactory result.
Opis
Słowa kluczowe
energy use intensity, neural networks, statistical prediction, intensywność zużycia energii, sieci neuronowe, predykcja statystyczna
Cytowanie
Stokfiszewski K., Sztoch P., Sztoch R., Wosiak A., Building Energy Use Intensity Prediction with Artificial Neural Networks. W: Progress in Polish Artificial Intelligence Research 4, Wojciechowski A. (Ed.), Lipiński P. (Ed.)., Seria: Monografie Politechniki Łódzkiej Nr. 2437, Wydawnictwo Politechniki Łódzkiej, Łódź 2023, s. 313-318, ISBN 978-83-66741-92-8, doi: 10.34658/9788366741928.50.