Publications

2020

Wang, Zhe, and Tianzhen Hong."Learning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States."Renewable and Sustainable Energy Reviews 119 (2020) 109593. DOI
Hong, Tianzhen, Chien-Fei Chen, Zhe Wang, and Xiaojing Xu."Linking human-building interactions in shared offices with personality traits."Building and Environment 170 (2020) 106602. DOI
Li, Han, Tianzhen Hong, Sang Hoon Lee, and Marina Sofos."System-level key performance indicators for building performance evaluation."Energy and Buildings 209 (2020) 109703. DOI
Hong, Tianzhen, Yixing Chen, Xuan Luo, Na Luo, and Sang Hoon Lee."Ten questions on urban building energy modeling."Building and Environment 168 (2020) 106508. DOI
Piette, Mary Ann, Richard C. Diamond, Stephen E. Selkowitz, Stephane de la Rue du Can, Tianzhen Hong, Kaiyu Sun, Paul A. Mathew, Iain S. Walker, Alan K. Meier, Erik Page, Jessica Granderson, Nan Zhou, and Peter Alstone."Chapter 2: Global Opportunities and Challenges in Energy and Environmental Issues in the Buildings Sector."World Scientific Series in Current Energy Issues (2020). DOI

2019

Hong, Tianzhen, Yujie Xu, Kaiyu Sun, Wanni Zhang, and Xuan Luo."Visualizing Urban Microclimate and Quantifying its Impact on Building Energy Use in San Francisco."the 1st ACM International WorkshopProceedings of the 1st ACM International Workshop on Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization - UrbSys'19 (2019). DOI
Karaguzel, Omer T., Mohammed Elshambakey, Yimin Zhu, and Tianzhen Hong."OPEN COMPUTING INFRASTRUCTURE FOR SHARING DATA ANALYTICS TO SUPPORT BUILDING ENERGY SIMULATIONS." (2019).
Xu, Xiaodong, Wei Wang, Tianzhen Hong, and Jiayu Chen."Incorporating machine learning with building network analysis to predict multi-building energy use."Energy and Buildings 186 (2019) 80 - 97. DOI
Wang, Zhe, Tianzhen Hong, Mary Ann Piette, and Marco Pritoni."Inferring occupant counts from Wi-Fi data in buildings through machine learning."Building and Environment 158 (2019) 281 - 294. DOI
Hong, Tianzhen, and Sang Hoon Lee."Integrating physics-based models with sensor data: An inverse modeling approach."Building and Environment 154 (2019) 23 - 31. DOI
Wang, Zhe, Tianzhen Hong, and Mary Ann Piette."Predicting plug loads with occupant count data through a deep learning approach."Energy 181 (2019) 29 - 42. DOI
Wang, Wei, Tianzhen Hong, Xiaodong Xu, Jiayu Chen, Ziang Liu, and Ning Xu."Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm."Applied Energy 248 (2019) 217 - 230. DOI
Guo, Siyue, Da Yan, Tianzhen Hong, Chan Xiao, and Ying Cui."A novel approach for selecting typical hot-year (THY) weather data."Applied Energy 242 (2019) 1634 - 1648. DOI
Xu, Xiaodong, Yifan Wu, Wei Wang, Tianzhen Hong, and Ning Xu."Performance-driven optimization of urban open space configuration in the cold-winter and hot-summer region of China."Building Simulation 12.3 (2019) 411 - 424. DOI
Wang, Zhe, Thomas Parkinson, Peixian Li, Borong Lin, and Tianzhen Hong."The Squeaky wheel: Machine learning for anomaly detection in subjective thermal comfort votes."Building and Environment 151 (2019) 219 - 227. DOI
Jia, Ruoxi, Ming Jin, Kaiyu Sun, Tianzhen Hong, and Costas Spanos."Advanced Building Control via Deep Reinforcement Learning."Energy Procedia 158 (2019) 6158 - 6163. DOI
Wang, Zhe, Tianzhen Hong, and Mary Ann Piette."Data fusion in predicting internal heat gains for office buildings through a deep learning approach."Applied Energy 240 (2019) 386 - 398. DOI
Wang, Wei, Tianzhen Hong, Nan Li, Ryan Qi Wang, and Jiayu Chen."Linking energy-cyber-physical systems with occupancy prediction and interpretation through WiFi probe-based ensemble classification."Applied Energy 236 (2019) 55 - 69. DOI
Luo, Na, Wenguo Weng, Xiaoyu Xu, Tianzhen Hong, Ming Fu, and Kaiyu Sun."Assessment of occupant-behavior-based indoor air quality and its impacts on human exposure risk: A case study based on the wildfires in Northern California."Science of The Total Environment 686 (2019) 1251 - 1261. DOI
Wang, , Wei, Tianzhen Hong, Ning Xu, Xiaodong Xu, Jiayu Chen, and Xiaofang Shan."Cross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering."Building and Environment 162 (2019) 106280. DOI
Li, , Han, Tianzhen Hong, and Marina Sofos."An inverse approach to solving zone air infiltration rate and people count using indoor environmental sensor data."Energy and Buildings 198 (2019) 228 - 242. DOI
Wang, Zhe, and Tianzhen Hong."Learning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States."Renewable and Sustainable Energy Reviews (2019) 109593. DOI
Xu, , Xiaodong, Chenhuan Yin, Wei Wang, Ning Xu, Tianzhen Hong, and Qi Li."Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China."Sustainability 11.13 (2019) 3683. DOI
Lee, , Sang Hoon, and Tianzhen Hong."Validation of an inverse model of zone air heat balance."Building and Environment 161 (2019) 106232. DOI
Chen, Yixing, Tianzhen Hong, Xuan Luo, and Barry Hooper."Development of city buildings dataset for urban building energy modeling."Energy and Buildings 183 (2019) 252 - 265. DOI