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Zhe (Walter) WANG
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Individual difference in thermal comfort: A literature review
Z Wang, R de Dear, M Luo, B Lin, Y He, A Ghahramani, Y Zhu
Building and Environment 138, 181-193, 2018
5512018
Reinforcement learning for building controls: The opportunities and challenges
Z Wang, T Hong
Applied Energy 269, 115036, 2020
3812020
Building thermal load prediction through shallow machine learning and deep learning
Z Wang, T Hong, MA Piette
Applied Energy 263, 114683, 2020
3102020
A review of operating performance in green buildings: Energy use, indoor environmental quality and occupant satisfaction
Y Geng, W Ji, Z Wang, B Lin, Y Zhu
Energy and Buildings 183, 500-514, 2019
2992019
State-of-the-art on research and applications of machine learning in the building life cycle
T Hong, Z Wang, X Luo, W Zhang
Energy and Buildings 212, 109831, 2020
2572020
Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications
H Li, Z Wang, T Hong, MA Piette
Advances in Applied Energy 3, 100054, 2021
2222021
Human metabolic rate and thermal comfort in buildings: The problem and challenge
M Luo, Z Wang, K Ke, B Cao, Y Zhai, X Zhou
Building and Environment 131, 44-52, 2018
1932018
Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives
G Pinto, Z Wang, A Roy, T Hong, A Capozzoli
Advances in Applied Energy 5, 100084, 2022
1612022
Evaluation and comparison of thermal comfort of convective and radiant heating terminals in office buildings
B Lin, Z Wang, H Sun, Y Zhu, Q Ouyang
Building and Environment 106, 91-102, 2016
1602016
Thermal comfort evaluated for combinations of energy-efficient personal heating and cooling devices
M Luo, E Arens, H Zhang, A Ghahramani, Z Wang
Building and Environment 143, 206-216, 2018
1372018
High-density thermal sensitivity maps of the human body
M Luo, Z Wang, H Zhang, E Arens, D Filingeri, L Jin, A Ghahramani, ...
Building and environment 167, 106435, 2020
1172020
Indoor climate experience, migration, and thermal comfort expectation in buildings
M Luo, Z Wang, G Brager, B Cao, Y Zhu
Building and Environment 141, 262-272, 2018
1132018
Investigation of winter indoor thermal environment and heating demand of urban residential buildings in China's hot summer–Cold winter climate region
B Lin, Z Wang, Y Liu, Y Zhu, Q Ouyang
Building and Environment 101, 9-18, 2016
1082016
Residential heating energy consumption modeling through a bottom-up approach for China's Hot Summer–Cold Winter climatic region
Z Wang, Z Zhao, B Lin, Y Zhu, Q Ouyang
Energy and Buildings 109, 65-74, 2015
1002015
Data fusion in predicting internal heat gains for office buildings through a deep learning approach
Z Wang, T Hong, MA Piette
Applied Energy 240, 386-398, 2019
972019
Measured energy use and indoor environment quality in green office buildings in China
B Lin, Y Liu, Z Wang, Z Pei, M Davies
Energy and Buildings 129, 9-18, 2016
912016
Revisiting individual and group differences in thermal comfort based on ASHRAE database
Z Wang, H Zhang, Y He, M Luo, Z Li, T Hong, B Lin
Energy and Buildings 219, 110017, 2020
872020
The uncertainty of subjective thermal comfort measurement
J Wang, Z Wang, R de Dear, M Luo, A Ghahramani, B Lin
Energy and Buildings 181, 38-49, 2018
872018
Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN)
Z Wang, T Hong
Energy and Buildings 224, 110299, 2020
862020
Dimension analysis of subjective thermal comfort metrics based on ASHRAE Global Thermal Comfort Database using machine learning
Z Wang, J Wang, Y He, Y Liu, B Lin, T Hong
Journal of Building Engineering 29, 101120, 2020
852020
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