Yongbao Chen 
- (2023): An XGBoost-Based predictive control strategy for HVAC systems in providing day-ahead demand response. Dans: Building and Environment, v. 238 (juin 2023).
- (2023): Machine Learning Approach to Predict Building Thermal Load Considering Feature Variable Dimensions: An Office Building Case Study. Dans: Buildings, v. 13, n. 2 (14 février 2023).
- (2023): Physics-informed neural networks for building thermal modeling and demand response control. Dans: Building and Environment, v. 234 (avril 2023).
- (2022): Optimal Control Strategies for Demand Response in Buildings under Penetration of Renewable Energy. Dans: Buildings, v. 12, n. 3 (8 mars 2022).
- (2022): Multi-objective residential load scheduling approach for demand response in smart grid. Dans: Sustainable Cities and Society, v. 76 (janvier 2022).
- (2021): A novel short-term load forecasting framework based on time-series clustering and early classification algorithm. Dans: Energy and Buildings, v. 251 (novembre 2021).
- (2019): A simplified HVAC energy prediction method based on degree-day. Dans: Sustainable Cities and Society, v. 51 (novembre 2019).
- (2017): Research on the performance of an adsorption heat pump in winter demand response. Dans: Science and Technology for the Built Environment, v. 23, n. 3 (février 2017).
- (2020): Short-term metropolitan-scale electric load forecasting based on load decomposition and ensemble algorithms. Dans: Energy and Buildings, v. 225 (octobre 2020).
- (2018): Measures to improve energy demand flexibility in buildings for demand response (DR): A review. Dans: Energy and Buildings, v. 177 (octobre 2018).
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