Article ID Journal Published Year Pages File Type
4911535 Building and Environment 2017 11 Pages PDF
Abstract
High acceptability was found at home, restaurants and workplaces, whereas low acceptability was found for outdoor and transport environments. The participants, from Singapore's modern tropical environment spent an average of 96% of their time indoors. Weak associations were reported between acceptabilities and measured physical parameters taken independently. Clustering data by location, subject's sleeping ventilation habit, air-conditioning operation status and the changes in physical parameters over a designated time period enhanced the understanding of the acceptability results. In general, acceptability was lower for those who slept in air-conditioned environments than for those who slept without air-conditioning. The carbon dioxide mixing ratio was critical for PAQA predictions but not for TA. The Gaussian process (GP) had a better predictive power than a multiple linear regression approach. Using GP, we found that a general predictive model had comparable simulation performance as for individual predictive models. The longitudinal experiment has demonstrated effectiveness for TA and PAQA analysis, which could be beneficial to future studies in personal comfort prediction.
Keywords
Related Topics
Physical Sciences and Engineering Energy Renewable Energy, Sustainability and the Environment
Authors
, , , , ,