THERMAL SCIENCE

International Scientific Journal

Aleksandra A. Sretenović

,

Radiša Ž Jovanović

,

Vojislav M. Novaković

,

Nataša M. Nord

,

Branislav Živković

SUPPORT VECTOR MACHINE FOR THE PREDICTION OF HEATING ENERGY USE

ABSTRACT
Prediction of a building energy use for heating is very important for adequate energy planning. In this paper the daily district heating use of one university campus was predicted using the support vector machine model. Support vector machine is the artificial intelligence method that has recently proved that it can achieve comparable, or even better prediction results than the much more used artificial neural networks. The proposed model was trained and tested on the real, measured data. The model accuracy was compared with the results of the previously published models (various neural networks and their ensembles) on the same database. The results showed that the support vector machine model can achieve better results than the individual neural networks, but also better than the conventional and multistage ensembles. It is expected that this theoretically well-known methodology finds wider application, especially in prediction tasks.
KEYWORDS
heating use prediction, support vector machine, artificial intelligence models
PAPER SUBMITTED: 2017-05-26
PAPER REVISED: 2017-10-25
PAPER ACCEPTED: 2017-12-11
PUBLISHED ONLINE: 2018-04-28
DOI REFERENCE: https://doi.org/10.2298/TSCI170526126S
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2018, VOLUME 22, ISSUE Supplement 4, PAGES [S1171 - S1181]
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Support vector machine for the prediction of heating energy use

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