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 | 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 | 47 - View on Scopus |
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