Wenping Xue 
- (2024): Developing a novel personal thermoelectric comfort system for improving indoor occupant’s thermal comfort. In: Journal of Building Engineering, v. 84 (Mai 2024).
- (2024): Data efficient indoor thermal comfort prediction using instance based transfer learning method. In: Energy and Buildings, v. 306 (März 2024).
- (2024): An instance based multi-source transfer learning strategy for building’s short-term electricity loads prediction under sparse data scenarios. In: Journal of Building Engineering, v. 85 (Mai 2024).
- (2023): Non-invasive human thermal comfort assessment based on multiple angle/distance facial key-region temperatures recognition. In: Building and Environment, v. 246 (Dezember 2023).
- (2023): Fast reconstruction of indoor temperature field for large-space building based on limited sensors: An experimental study. In: Energy and Buildings, v. 298 (November 2023).
- (2023): Correlation analysis and modeling of human thermal sensation with multiple physiological markers: An experimental study. In: Energy and Buildings, v. 278 (Januar 2023).
- (2022): Building’s hourly electrical load prediction based on data clustering and ensemble learning strategy. In: Energy and Buildings, v. 261 (April 2022).
- (2021): An adaptive ensemble predictive strategy for multiple scale electrical energy usages forecasting. In: Sustainable Cities and Society, v. 66 (März 2021).
- (2019): A state of the art review on the prediction of building energy consumption using data-driven technique and evolutionary algorithms. In: Building Services Engineering Research and Technology, v. 41, n. 1 (Dezember 2019).
- (2021): Short-term electricity consumption prediction for buildings using data-driven swarm intelligence based ensemble model. In: Energy and Buildings, v. 231 (Januar 2021).
- (2013): Optimization of ventilation system operation in office environment using POD model reduction and genetic algorithm. In: Energy and Buildings, v. 67 (Dezember 2013).
- (2015): Building's electricity consumption prediction using optimized artificial neural networks and principal component analysis. In: Energy and Buildings, v. 108 (Dezember 2015).
- (2018): A hybrid teaching-learning artificial neural network for building electrical energy consumption prediction. In: Energy and Buildings, v. 174 (September 2018).
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