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Journal of Building Performance Simulation Volume 5, 2012 - Issue 4
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Articles

Kernel regression for real-time building energy analysis

Matthew Brown Department of Computer Science, École Polytechnique Fédérale de Lausanne, SwitzerlandCorrespondence[email protected]
,
Chris Barrington-Leigh Department of Economics, University of British Columbia, Vancouver, Canada
&
Zosia Brown† Resource Management and Environmental Studies, University of British Columbia, Vancouver, CanadaView further author information
Pages 263-276 | Received 06 Nov 2010, Accepted 30 Mar 2011, Published online: 16 Jun 2011

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Peng Liang, Hai-Dong Yang, Wen-Si Chen, Si-Yuan Xiao & Zhao-Ze Lan. (2018) Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks. International Journal of Computer Integrated Manufacturing 31:4-5, pages 396-405.
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Miguel Mora, Semiha Ergan, Hanzhi Chen, Hengfang Deng, An-Lei Huang, Jared Maurer & Nan Wang. (2015) Learning about Performance of Building Systems and Facility Operations through a Capstone Project Course. Learning about Performance of Building Systems and Facility Operations through a Capstone Project Course.
Jui-Sheng Chou & Abdi Suryadinata Telaga. (2014) Real-time detection of anomalous power consumption. Renewable and Sustainable Energy Reviews 33, pages 400-411.
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Pieter de Wilde, Carlos Martinez-Ortiz, Darren Pearson, Ian Beynon, Martin Beck & Nigel Barlow. (2013) Building simulation approaches for the training of automated data analysis tools in building energy management. Advanced Engineering Informatics 27:4, pages 457-465.
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Alexander Severinsen & Øystein Myrland. (2022) Statistical Learning to Estimate Energy Savings from Retrofitting in the Norwegian Food Retail Market. SSRN Electronic Journal.
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