- Damage assessment and diagnosis of hydraulic concrete structures using optimization-based machine learning technology. In: Frontiers of Structural and Civil Engineering, v. 17, n. 8 (August 2023). (2023):
- Analysis of urban turbulence intensity observed by Beijing 325-m tower and comparison with the IEC turbulence model for small wind turbines. In: Journal of Wind Engineering and Industrial Aerodynamics, v. 241 (October 2023). (2023):
- A Coupled Model for Dam Foundation Seepage Behavior Monitoring and Forecasting Based on Variational Mode Decomposition and Improved Temporal Convolutional Network. In: Structural Control and Health Monitoring, v. 2023 (February 2023). (2023):
- A mathematical-mechanical hybrid driven approach for determining the deformation monitoring indexes of concrete dam. In: Engineering Structures, v. 277 (February 2023). (2023):
- An integrated underwater structural multi-defects automatic identification and quantification framework for hydraulic tunnel via machine vision and deep learning. In: Structural Health Monitoring, v. 22, n. 4 (December 2022). (2022):
- Underwater crack pixel-wise identification and quantification for dams via lightweight semantic segmentation and transfer learning. In: Automation in Construction, v. 144 (December 2022). (2022):
- Dam safety assessment through data-level anomaly detection and information fusion. In: Structural Health Monitoring, v. 22, n. 3 (September 2022). (2022):
- Unsupervised dam anomaly detection with spatial–temporal variational autoencoder. In: Structural Health Monitoring, v. 22, n. 1 (November 2019). (2019):
- Data-driven crack behavior anomaly identification method for concrete dams in long-term service using offline and online change point detection. In: Journal of Civil Structural Health Monitoring, v. 11, n. 5 (6 September 2021). (2021):
- Fast elimination of cable fire smoke in underground tunnels using acoustic agglomeration technology. In: Tunnelling and Underground Space Technology, v. 117 (November 2021). (2021):
- A new dam structural response estimation paradigm powered by deep learning and transfer learning techniques. In: Structural Health Monitoring, v. 21, n. 3 (August 2021). (2021):
- Generating layout designs from high-level specifications. In: Automation in Construction, v. 119 (November 2020). (2020):
- Customization and generation of floor plans based on graph transformations. In: Automation in Construction, v. 94 (October 2018). (2018):