Personal comfort models: Predicting individuals' thermal preference using occupant heating and cooling behavior and machine learning-Reference-Cited by-同舟云学术

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Personal comfort models: Predicting individuals' thermal preference using occupant heating and cooling behavior and machine learning

Published:2018-02 Issue: Volume:129 Page:96-106
ISSN:0360-1323
Container-title:Building and Environment
language:en
Short-container-title:Building and Environment

Author:

Kim Joyce^ORCID,Zhou Yuxun,Schiavon Stefano^ORCID,Raftery Paul,Brager Gail

Funder

California Energy Commission Public Interest Energy Research (PIER)

Center for the Built Environment at University of California, Berkeley

Publisher

Elsevier BV

Subject

Building and Construction,Geography, Planning and Development,Civil and Structural Engineering,Environmental Engineering

Reference69 articles.

1. Thermal comfort and workplace occupant satisfaction - results of field studies in German low energy office buildings;Wagner;Energy Build.,2007

2. Quantitative relationships between occupant satisfaction and satisfaction aspects of indoor environmental quality and building design;Frontczak;Indoor Air,2012

3. Estimates of improved productivity and health from better indoor environments;Fisk;Indoor Air,1997

4. Green buildings and health;Allen;Curr. Environ. Health Rep.,2015

5. Productivity in buildings: the ‘killer’ variables;Leaman;Build. Res. Inf.,1999

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