Advancing personal thermal comfort prediction: A data-driven framework integrating environmental and occupant dynamics using machine learning-Reference-Cited by-同舟云学术

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Advancing personal thermal comfort prediction: A data-driven framework integrating environmental and occupant dynamics using machine learning

Published:2024-08 Issue: Volume:262 Page:111799
ISSN:0360-1323
Container-title:Building and Environment
language:en
Short-container-title:Building and Environment

Author:

Haghirad Maedeh^ORCID,Heidari Shahin,Hosseini Hojat^ORCID

Publisher

Elsevier BV

Reference72 articles.

1. The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants;Klepeis;J. Exp. Sci. Environ. Epidemiol.,2001

2. Occupancy behavior based model predictive control for building indoor climate—A critical review;Mirakhorli;Energy Build.,2016

3. Thermal environmental conditions for human occupancy;Lynch;ASHRAE J.,1966

4. Dynamic characteristics and comfort assessment of airflows in indoor environments: A review;Zhu;Build. Environ.,2015

5. Thermal comfort under radiant asymmetries of floor cooling system in 2h and 8h exposure durations;Zhou;Energy Build.,2019

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