Yabin Guo 
- (2024): Three-stage numerical simulation of tunnel blasting dust diffusion based on field monitoring and CFD. Dans: Tunnelling and Underground Space Technology, v. 150 (août 2024).
- (2024): Research on fault detection and diagnosis of carbon dioxide heat pump systems in buildings based on transfer learning. Dans: Journal of Building Engineering, v. 85 (mai 2024).
- (2023): An advanced ensemble clustering approach for data partitioning and mining to optimize performance in variable refrigerant flow systems. Dans: Journal of Building Engineering, v. 78 (novembre 2023).
- (2016): A sensor fault detection and diagnosis strategy for screw chiller system using support vector data description-based D-statistic and DV-contribution plots. Dans: Energy and Buildings, v. 133 (décembre 2016).
- (2017): An enhanced PCA method with Savitzky-Golay method for VRF system sensor fault detection and diagnosis. Dans: Energy and Buildings, v. 142 (mai 2017).
- (2017): Identification and isolation of outdoor fouling faults using only built-in sensors in variable refrigerant flow system: A data mining approach. Dans: Energy and Buildings, v. 146 (juillet 2017).
- (2017): Optimization of support vector regression model based on outlier detection methods for predicting electricity consumption of a public building WSHP system. Dans: Energy and Buildings, v. 151 (septembre 2017).
- (2018): A machine learning bayesian network for refrigerant charge faults of variable refrigerant flow air conditioning system. Dans: Energy and Buildings, v. 158 (janvier 2018).
- (2018): A comprehensive overview on the data driven and large scale based approaches for forecasting of building energy demand: A review. Dans: Energy and Buildings, v. 165 (avril 2018).
- (2021): New fault diagnostic strategies for refrigerant charge fault in a VRF system using hybrid machine learning method. Dans: Journal of Building Engineering, v. 33 (janvier 2021).
- (2019): Improving prediction performance for indoor temperature in public buildings based on a novel deep learning method. Dans: Building and Environment, v. 148 (janvier 2019).
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