Short and medium-term forecasting of cooling and heating load demand in building environment with data-mining based approaches

Short and medium-term forecasting of cooling and heating load demand in building environment with... •The basic objective of this research is to predict the future cooling load demand of WSHP.•Six novel data mining-based models were proposed for forecasting the cooling load.•Six performance indices are used to evaluate the prediction performance of models.•MAPE results for 7-day future load forecasting were 3.544%, 0.405%, 1.703%, 1.928%, 2.592% and 13.053%, respectively of six DM models.•Proposed models compared with the existing model BRNN and the MAPE found 2.515% for 7-day. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Energy and Buildings Elsevier

Short and medium-term forecasting of cooling and heating load demand in building environment with data-mining based approaches

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier B.V.
ISSN
0378-7788
eISSN
1872-6178
D.O.I.
10.1016/j.enbuild.2018.01.066
Publisher site
See Article on Publisher Site

Abstract

•The basic objective of this research is to predict the future cooling load demand of WSHP.•Six novel data mining-based models were proposed for forecasting the cooling load.•Six performance indices are used to evaluate the prediction performance of models.•MAPE results for 7-day future load forecasting were 3.544%, 0.405%, 1.703%, 1.928%, 2.592% and 13.053%, respectively of six DM models.•Proposed models compared with the existing model BRNN and the MAPE found 2.515% for 7-day.

Journal

Energy and BuildingsElsevier

Published: May 1, 2018

References

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