Limao Zhang 
- : A transformer-based deep learning method for automatic pixel-level crack detection and feature quantification. In: Engineering, Construction and Architectural Management.
- (2023): Time series clustering-enabled geological condition perception in tunnel boring machine excavation. In: Automation in Construction, v. 153 (September 2023).
- (2023): Time series prediction of tunnel boring machine (TBM) performance during excavation using causal explainable artificial intelligence (CX-AI). In: Automation in Construction, v. 147 (März 2023).
- (2022): UnrollingNet: An attention-based deep learning approach for the segmentation of large-scale point clouds of tunnels. In: Automation in Construction, v. 142 (Oktober 2022).
- (2021): Vulnerability modeling, assessment, and improvement in urban metro systems: A probabilistic system dynamics approach. In: Sustainable Cities and Society, v. 75 (Dezember 2021).
- (2018): Valuation of energy efficient certificates in buildings. In: Energy and Buildings, v. 158 (Januar 2018).
- (2020): A two-step approach for cost-effective design analysis of Net Zero Energy Homes. In: Journal of Building Engineering, v. 32 (November 2020).
- (2014): Towards a safety management approach for adjacent buildings in tunneling environments: Case study in China. In: Building and Environment, v. 75 (Mai 2014).
- (2019): Understanding Critical Variables Contributing To Competitive Advantages of International High-speed Railway Contractors. In: Journal of Civil Engineering and Management, v. 25, n. 2 (Mai 2019).
Structurae kooperiert mit
