Ke Yan 
- : Semi-supervised CWGAN-GP modeling for AHU AFDD with high-quality synthetic data filtering mechanism. In: Building and Environment.
- (2024): Household energy consumption forecasting based on adaptive signal decomposition enhanced iTransformer network. In: Energy and Buildings, v. 324 (Dezember 2024).
- (2024): 3D reconstruction of semantic-rich digital twins for ACMV monitoring and anomaly detection via scan-to-BIM and time-series data integration. In: Developments in the Built Environment, v. 19 (Oktober 2024).
- (2024): Ensemble learning based multi-fault diagnosis of air conditioning system. In: Energy and Buildings, v. 319 (September 2024).
- (2024): SS-CWGAN: A novel fault diagnosis model for building HVAC systems under limited labeled data. In: Energy and Buildings, v. 319 (September 2024).
- (2024): Inverse machine learning framework for optimizing gradient honeycomb structure under impact loading. In: Engineering Structures, v. 309 (Juni 2024).
- (2024): Blast mitigation effects of TPU polymers-based inflated membrane structures under external explosion. In: Construction and Building Materials, v. 427 (Mai 2024).
- (2024): Study on the mechanical properties and ballistic resistance of interface-modified fabrics with environmentally friendly shear thickening liquid. In: Composite Structures, v. 337 (Juni 2024).
- (2024): Chiller fault diagnosis based on improved variational autoencoder and co-training framework: A case study of insufficient samples. In: Journal of Building Engineering, v. 88 (Juli 2024).
- (2024): An interpretable feature selection method integrating ensemble models for chiller fault diagnosis. In: Journal of Building Engineering, v. 87 (Juni 2024).
- (2023): AI and IoT applications of smart buildings and smart environment design, construction and maintenance. In: Building and Environment, v. 229 (Februar 2023).
- (2022): Data-driven prediction and optimization of residential building performance in Singapore considering the impact of climate change. In: Building and Environment, v. 226 (Dezember 2022).
- (2022): A solar forecasting framework based on federated learning and distributed computing. In: Building and Environment, v. 225 (November 2022).
- (2022): A model developed for predicting thermal comfort during sleep in response to appropriate air velocity in warm environments. In: Building and Environment, v. 223 (September 2022).
- (2022): Optimization and prediction in the early design stage of office buildings using genetic and XGBoost algorithms. In: Building and Environment, v. 218 (Juni 2022).
- (2022): Comparison of models for predicting winter individual thermal comfort based on machine learning algorithms. In: Building and Environment, v. 215 (Mai 2022).
- (2021): Probabilistic graphical models in energy systems: A review. In: Building Simulation, v. 15, n. 5 (Oktober 2021).
- (2021): Characteristics and comfort evaluation of sinusoidal airflows by regulating motor rotating frequency of a floor fan. In: Building Simulation, v. 15, n. 6 (Dezember 2021).
- (2021): Occupancy-based energy consumption modelling using machine learning algorithms for institutional buildings. In: Energy and Buildings, v. 252 (Dezember 2021).
- (2021): Chiller fault detection and diagnosis with anomaly detective generative adversarial network. In: Building and Environment, v. 201 (August 2021).
- (2014): ARX model based fault detection and diagnosis for chillers using support vector machines. In: Energy and Buildings, v. 81 (Oktober 2014).
- (2015): Robust model-based fault diagnosis for air handling units. In: Energy and Buildings, v. 86 (Januar 2015).
- (2020): Unsupervised learning for fault detection and diagnosis of air handling units. In: Energy and Buildings, v. 210 (März 2020).
- (2018): Semi-supervised learning for early detection and diagnosis of various air handling unit faults. In: Energy and Buildings, v. 181 (Dezember 2018).
- (2020): Generative adversarial network for fault detection diagnosis of chillers. In: Building and Environment, v. 172 (April 2020).
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