- Effects of various information scenarios on layer-wise relevance propagation-based interpretable convolutional neural networks for air handling unit fault diagnosis. In: Building Simulation. :
- A novel global modelling strategy integrated dynamic kernel canonical variate analysis for the air handling unit fault detection via considering the two-directional dynamics. In: Journal of Building Engineering, v. 96 (November 2024). (2024):
- An improved BIM aided indoor localization method via enhancing cross-domain image retrieval based on deep learning. In: Journal of Building Engineering, v. 91 (August 2024). (2024):
- Imbalanced data based fault diagnosis of the chiller via integrating a new resampling technique with an improved ensemble extreme learning machine. In: Journal of Building Engineering, v. 70 (July 2023). (2023):
- Images based fault diagnosis of air handling unit via combining kernel slow feature analysis and deep learning method. In: Journal of Building Engineering, v. 56 (September 2022). (2022):
- Fault detection and diagnosis of the air handling unit via combining the feature sparse representation based dynamic SFA and the LSTM network. In: Energy and Buildings, v. 269 (August 2022). (2022):
- Fault detection and diagnosis of the air handling unit via an enhanced kernel slow feature analysis approach considering the time-wise and batch-wise dynamics. In: Energy and Buildings, v. 253 (December 2021). (2021):
- A novel temporal convolutional network via enhancing feature extraction for the chiller fault diagnosis. In: Journal of Building Engineering, v. 42 (October 2021). (2021):