Prediction of residential building occupancy using Machine learning with integrated sensor and survey Data: Insights from a living lab in Morocco-Reference-Cited by-同舟云学术

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Prediction of residential building occupancy using Machine learning with integrated sensor and survey Data: Insights from a living lab in Morocco

Published:2024-09 Issue: Volume:319 Page:114519
ISSN:0378-7788
Container-title:Energy and Buildings
language:en
Short-container-title:Energy and Buildings

Author:

Bouyakhsaine Khadija,Brakez Abderrahim,Draou Mohcine

Publisher

Elsevier BV

Reference64 articles.

1. ANSIIASHRAE/IES Standard 90.1-2010, Energy Standard for Buildings Except Low-Rise Residential Buildings (I-P Edition), (n.d.).

2. D. Yan, T. Hong, Definition and Simulation of Occupant Behavior in Buildings, (n.d.). https://www.annex66.org/.

3. IEA EBC Annex 66: Definition and simulation of occupant behavior in buildings;Yan;Energy Build.,2017

4. Introducing IEA EBC annex 79: Key challenges and opportunities in the field of occupant-centric building design and operation;O’Brien;Build. Environ.,2020

5. A systematic procedure to study the influence of occupant behavior on building energy consumption;Yu;Energy Build.,2011

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1. Modelling occupant behaviour in residential buildings: A systematic literature review;Building and Environment;2024-11

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