Intelligent forecasting of residential heating demand for the District Heating System based on the monthly overall natural gas consumption

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Izadyar, Nima ORCID: 0000-0002-2487-5915, Ong, HC, Shamshirband, S, Ghadamian, H and Tong, CW (2015) Intelligent forecasting of residential heating demand for the District Heating System based on the monthly overall natural gas consumption. Energy and Buildings, 104. pp. 208-214. ISSN 0378-7788

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/42607
DOI https://doi.org/10.1016/j.enbuild.2015.07.006
Official URL https://www.sciencedirect.com/science/article/pii/...
Subjects Current > FOR (2020) Classification > 3302 Building
Current > FOR (2020) Classification > 4602 Artificial intelligence
Current > Division/Research > College of Science and Engineering
Keywords energy demand; energy consumption prediction; Extreme Learning Machine; artificial neural networks; genetic programming
Citations in Scopus 31 - View on Scopus
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