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Development of an England-wide indoor overheating and air pollution model using artificial neural networks

Symonds, PH; Taylor, J; Chalabi, Z; Mavrogianni, A; Davies, M; Hamilton, I; Vardoulakis, S; ... Macintyre, H; + view all (2016) Development of an England-wide indoor overheating and air pollution model using artificial neural networks. Journal of Building Performance Simulation , 9 (6) pp. 606-619. 10.1080/19401493.2016.1166265. Green open access

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Abstract

With the UK climate projected to warm in future decades, there is an increased research focus on the risks of indoor overheating. Energy-efficient building adaptations may modify a buildings risk of overheating and the infiltration of air pollution from outdoor sources. This paper presents the development of a national model of indoor overheating and air pollution, capable of modelling the existing and future building stocks, along with changes to the climate, outdoor air pollution levels, and occupant behaviour. The model presented is based on a large number of EnergyPlus simulations run in parallel. A metamodelling approach is used to create a model that estimates the indoor overheating and air pollution risks for the English housing stock. The performance of neural networks (NNs) is compared to a support vector regression (SVR) algorithm when forming the metamodel. NNs are shown to give almost a 50% better overall performance than SVR.

Type: Article
Title: Development of an England-wide indoor overheating and air pollution model using artificial neural networks
Location: UK
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/19401493.2016.1166265
Publisher version: http://dx.doi.org/10.1080/19401493.2016.1166265
Language: English
Additional information: This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Building Performance Simulation on 13 April 2016, available online: http://www.tandfonline.com/10.1080/19401493.2016.1166265.
Keywords: Metamodelling, machine learning, neural networks, stock modelling, overheating, indoor air pollution
UCL classification: UCL > School of BEAMS
UCL > School of BEAMS > Faculty of the Built Environment
URI: http://discovery.ucl.ac.uk/id/eprint/1482123
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