Danyang Di
- Intelligent prediction model of a polymer fracture grouting effect based on a genetic algorithm-optimized back propagation neural network. In: Tunnelling and Underground Space Technology, v. 148 (June 2024). (2024):
- Mechanical characteristics of concrete pipes under the coupled effects of the pressure, seepage, and flow fields. In: Structures, v. 61 (March 2024). (2024):
- Shear behavior of a two-component non-water reactive foamed polyurethane (TNFPU) grouting material under different stress levels. In: Construction and Building Materials, v. 411 (January 2024). (2024):
- Using EPS and CFRP liner to strengthen prestressed concrete cylinder pipe. In: Construction and Building Materials, v. 412 (January 2024). (2024):
- An automatic defect classification and segmentation method on three-dimensional point clouds for sewer pipes. In: Tunnelling and Underground Space Technology, v. 143 (January 2024). (2024):
- Integrating fluid–solid coupling domain knowledge with deep learning models: An automatic and interpretable diagnostic system for the silting disease of drainage pipelines. In: Tunnelling and Underground Space Technology, v. 142 (December 2023). (2023):
- Defects identification and location of underground space for ground penetrating radar based on deep learning. In: Tunnelling and Underground Space Technology, v. 140 (October 2023). (2023):
- An automatic and integrated self-diagnosing system for the silting disease of drainage pipelines based on SSAE-TSNE and MS-LSTM. In: Tunnelling and Underground Space Technology, v. 136 (June 2023). (2023):