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