Appraisal of the support vector machine to forecast 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, Ghadamian, H, Ong, HC, moghadam, Z, Tong, CW and Shamshirband, S ORCID: 0000-0002-6605-498X (2015) Appraisal of the support vector machine to forecast residential heating demand for the District Heating System based on the monthly overall natural gas consumption. Energy, 93 (Part 2). pp. 1558-1567. ISSN 0360-5442

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/42608
DOI https://doi.org/10.1016/j.energy.2015.10.015
Official URL https://www.sciencedirect.com/science/article/pii/...
Subjects Current > FOR (2020) Classification > 3302 Building
Current > FOR (2020) Classification > 4017 Mechanical engineering
Current > Division/Research > College of Science and Engineering
Keywords natural gas demand; energy consumption; forecasting; artificial neural network; genetic programming
Citations in Scopus 42 - View on Scopus
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