Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6727309 | Energy and Buildings | 2018 | 38 Pages |
Abstract
In our case study, the Bagging model's R2 for TS, PMV, ET* and SET* were 0.4986, 0.9892, 0.9920 and 0.9900, respectively. It shows higher accuracy than SVM and ANN models in thermal perception prediction and outperforms the classical PMV index in TS prediction. Results indicate the proposed Bagging model's prediction performance is reliable and is highly accurate to predict the thermal perception.
Related Topics
Physical Sciences and Engineering
Energy
Renewable Energy, Sustainability and the Environment
Authors
Wu Zhibin, Li Nianping, Peng Jinqing, Cui Haijiao, Liu Penglong, Li Hongqiang, Li Xiwang,