Chaobo Zhang 
- (2023): An uncertainty-tolerant robust distributed control strategy for building cooling water systems considering measurement uncertainties. In: Journal of Building Engineering, v. 76 (Oktober 2023).
- (2023): Automated machine learning-based building energy load prediction method. In: Journal of Building Engineering, v. 80 (Dezember 2023).
- (2024): Automated data mining framework for building energy conservation aided by generative pre-trained transformers (GPT). In: Energy and Buildings, v. 305 (Februar 2024).
- (2024): Deformation prediction of large-scale civil structures using spatiotemporal clustering and empirical mode decomposition-based long short_term memory network. In: Automation in Construction, v. 158 (Februar 2024).
- (2023): Clustering compression-based computation-efficient calibration method for digital twin modeling of HVAC system. In: Building Simulation, v. 16, n. 6 (März 2023).
- (2022): Causal discovery-based external attention in neural networks for accurate and reliable fault detection and diagnosis of building energy systems. In: Building and Environment, v. 222 (August 2022).
- (2022): A general multi agent-based distributed framework for optimal control of building HVAC systems. In: Journal of Building Engineering, v. 52 (Juli 2022).
- (2022): Elastic weight consolidation-based adaptive neural networks for dynamic building energy load prediction modeling. In: Energy and Buildings, v. 265 (Juni 2022).
- (2022): Causal discovery and inference-based fault detection and diagnosis method for heating, ventilation and air conditioning systems. In: Building and Environment, v. 212 (März 2022).
- (2021): Federated learning-based short-term building energy consumption prediction method for solving the data silos problem. In: Building Simulation, v. 15, n. 6 (Dezember 2021).
- (2022): A semantic model-based fault detection approach for building energy systems. In: Building and Environment, v. 207 (Januar 2022).
- (2021): Probabilistic graphical models in energy systems: A review. In: Building Simulation, v. 15, n. 5 (Oktober 2021).
- (2021): Analytic hierarchy process-based fuzzy post mining method for operation anomaly detection of building energy systems. In: Energy and Buildings, v. 252 (Dezember 2021).
- (2021): A real-time abnormal operation pattern detection method for building energy systems based on association rule bases. In: Building Simulation, v. 15, n. 1 (29 September 2021).
- (2021): A knowledge-guided and data-driven method for building HVAC systems fault diagnosis. In: Building and Environment, v. 198 (Juli 2021).
- (2021): A multi agent-based optimal control method for combined cooling and power systems with thermal energy storage. In: Building Simulation, v. 14, n. 6 (April 2021).
- (2021): A comprehensive investigation of knowledge discovered from historical operational data of a typical building energy system. In: Journal of Building Engineering, v. 42 (Oktober 2021).
- (2021): Generic visual data mining-based framework for revealing abnormal operation patterns in building energy systems. In: Automation in Construction, v. 125 (Mai 2021).
- (2021): Simultaneous pixel-level concrete defect detection and grouping using a fully convolutional model. In: Structural Health Monitoring, v. 20, n. 4 (April 2021).
- (2020): A hybrid deep learning-based method for short-term building energy load prediction combined with an interpretation process. In: Energy and Buildings, v. 225 (Oktober 2020).
- (2020): A post mining method for extracting value from massive amounts of building operation data. In: Energy and Buildings, v. 223 (September 2020).
- (2019): A data mining-based method for revealing occupant behavior patterns in using mechanical ventilation systems of Dutch dwellings. In: Energy and Buildings, v. 193 (Juni 2019).
- (2019): A proactive fault detection and diagnosis method for variable-air-volume terminals in building air conditioning systems. In: Energy and Buildings, v. 183 (Januar 2019).
- (2020): Concrete bridge surface damage detection using a single‐stage detector. In: Computer-Aided Civil and Infrastructure Engineering, v. 35, n. 4 (4 März 2020).
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