Xilei Dai
- Developing smart air purifier control strategies for better IAQ and energy efficiency using reinforcement learning. In: Building and Environment, v. 242 (August 2023). (2023):
- Deciphering optimal mixed-mode ventilation in the tropics using reinforcement learning with explainable artificial intelligence. In: Energy and Buildings, v. 278 (Januar 2023). (2023):
- Building energy-consumption status worldwide and the state-of-the-art technologies for zero-energy buildings during the past decade. In: Energy and Buildings, v. 128 (September 2016). (2016):
- 2D-PIV measurement of range hood-driven flow in a domestic kitchen. In: Energy and Buildings, v. 177 (Oktober 2018). (2018):
- A review of studies applying machine learning models to predict occupancy and window-opening behaviours in smart buildings. In: Energy and Buildings, v. 223 (September 2020). (2020):
- Monte Carlo simulation to control indoor pollutants from indoor and outdoor sources for residential buildings in Tianjin, China. In: Building and Environment, v. 165 (November 2019). (2019):
- An artificial neural network model using outdoor environmental parameters and residential building characteristics for predicting the nighttime natural ventilation effect. In: Building and Environment, v. 159 (Juli 2019). (2019):
- Ventilation behavior in residential buildings with mechanical ventilation systems across different climate zones in China. In: Building and Environment, v. 143 (Oktober 2018). (2018):
- Long-term monitoring of indoor CO2 and PM2.5 in Chinese homes: Concentrations and their relationships with outdoor environments. In: Building and Environment, v. 144 (Oktober 2018). (2018):
- Indoor air quality and occupants' ventilation habits in China: Seasonal measurement and long-term monitoring. In: Building and Environment, v. 142 (September 2018). (2018):
- Modeling and controlling indoor formaldehyde concentrations in apartments: On-site investigation in all climate zones of China. In: Building and Environment, v. 127 (Januar 2018). (2018):