Occupancy-based energy consumption modelling using machine learning algorithms for institutional buildings

Occupancy information is one of the crucial variables in modelling and predicting the energy use in buildings. However, the presence of occupants is often stochastic in nature. In the presented case of eight space typologies derived from three institutional building blocks, a substantial variation i...

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Veröffentlicht in:	Energy and buildings 2021-12, Vol.252, p.111478, Article 111478
Hauptverfasser:	Anand, Prashant, Deb, Chirag, Yan, Ke, Yang, Junjing, Cheong, David, Sekhar, Chandra
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Building energy consumption Consumption patterns Deep neural network Energy consumption Energy efficiency Energy prediction Facilities management Fluorescent lamps Institutional Buildings Learning algorithms Lighting Machine learning Neural networks Occupancy Projectors Regression analysis Regression models Space type characterization Wi-Fi based Occupancy Count
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