Liu, Yiqiao and Chong, Wen Tong and Cao, Yijuan and Liu, Hongwei and Yu, Haowei and Cui, Tong and Chang, Li and Pan, Song (2022) Characteristics analysis and modeling of occupants' window operation behavior in hot summer and cold winter region, China. Building and Environment, 216. ISSN 0360-1323, DOI https://doi.org/10.1016/j.buildenv.2022.108998.
Full text not available from this repository.Abstract
Opening windows is an important factor when creating a comfortable indoor environment. However, research on window opening behavior in the Chinese region of hot summers and cold winters is limited. In addition, almost all previous research in this area has focused on the average characteristics of the sample mostly by building models of averageness, which largely erases individual behavioral attributes. To fill the gap, an empirical measurement and modeling study of window opening behavior was conducted in seven households in Zigong, Sichuan Province. The following was found: (1) The window opening behavior of residents in different cities in hot summer and cold winter regions significantly differed. The average daily duration of window opening by the test subjects in this paper is 1122 min/day, which is 2-5.5 times higher than previously published literature on this climate zone suggests. (2) Among the test subjects, three typical window opening behaviors were noticed based on the average daily window-opening probability (R), i.e., positive (R>95%), negative (R < 5%), and high intensity window opening (65% < R < 95%). The first two categories refer to personal habits of residents independent of environmental and temporal factors. (3) High-intensity window opening behavior provided imbalanced data which is more accurately modeled by the random forest model (98.9% prediction accuracy) than the binary logistic regression and decision tree models, i.e., 14.5% more accurate than the former and 12.5% more accurate than the latter. Moreover, it was found that the relative humidity indoors is the factor that contributed the most to the accuracy of the model.
| Item Type: | Article |
|---|---|
| Funders: | 13th Five-Year National Science and Technology Major Project of China (2016YFC0801706), 13th Five-Year National Science and Technology Major Project of China (2017YFC0702202), National Natural Science Foundation of China (NSFC) (51578011), International Science and Technology Cooperation Center in Hebei Province (20594501D) |
| Uncontrolled Keywords: | Typical window opening behavior; Average daily window-opening probability; Binary logistic regression; Decision tree; Random forest |
| Subjects: | N Fine Arts > NA Architecture T Technology > TA Engineering (General). Civil engineering (General) T Technology > TJ Mechanical engineering and machinery |
| Divisions: | Faculty of Engineering > Department of Mechanical Engineering Faculty of the Built Environment |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 10 Sep 2023 02:25 |
| Last Modified: | 10 Sep 2023 02:25 |
| URI: | http://eprints.um.edu.my/id/eprint/42961 |
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