- Design optimization of floor plan for public housing buildings in Hong Kong with consideration of natural ventilation, noise, and daylighting. Dans: Building and Environment, v. 263 (septembre 2024). (2024):
- Energy-efficient control of indoor PM2.5 and thermal comfort in a real room using deep reinforcement learning. Dans: Energy and Buildings, v. 295 (septembre 2023). (2023):
- Predicting spatial distribution of ultraviolet irradiance and disinfection of exhaled bioaerosols with a modified irradiance model. Dans: Building and Environment, v. 228 (janvier 2023). (2023):
- Smart control of window and air cleaner for mitigating indoor PM2.5 with reduced energy consumption based on deep reinforcement learning. Dans: Building and Environment, v. 224 (octobre 2022). (2022):
- A combined deep learning and physical modelling method for estimating air pollutants’ source location and emission profile in street canyons. Dans: Building and Environment, v. 219 (juillet 2022). (2022):
- Predicting transient particle transport in periodic ventilation using Markov chain model with pre-stored transition probabilities. Dans: Building and Environment, v. 211 (mars 2022). (2022):
- Exploring the feasibility of predicting contaminant transport using a stand-alone Markov chain solver based on measured airflow in enclosed environments. Dans: Building and Environment, v. 202 (septembre 2021). (2021):
- A reinforcement learning approach for control of window behavior to reduce indoor PM2.5 concentrations in naturally ventilated buildings. Dans: Building and Environment, v. 200 (août 2021). (2021):
- Modeling transient particle transport in transient indoor airflow by fast fluid dynamics with the Markov chain method. Dans: Building and Environment, v. 186 (décembre 2020). (2020):