Hybrid deep learning approach for rock tunnel deformation prediction based on spatio-temporal patterns
The ability to predict tunnel deformation holds great significance for ensuring the reliability, safety, and sustainability of tunnel structures. However, existing deformation prediction models often simplify or overlook the impact of spatial characteristics on deformation by treating it as a time s...
Saved in:
| Main Authors: | Junfeng Sun, Yong Fang, Hu Luo, Zhigang Yao, Long Xiang, Jianfeng Wang, Yubo Wang, Yifan Jiang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-02-01
|
| Series: | Underground Space |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2467967424000813 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A data-driven spatial-temporal model for prediction of tunnel deformation
by: Ziyi Zhang, et al.
Published: (2025-03-01) -
Research on prediction of surrounding rock deformation and optimization of construction parameters of high ground stress tunnel based on WOA-LSTM
by: Jianquan Yao, et al.
Published: (2024-11-01) -
Deep learning driven prediction and comparative study of surrounding rock deformation in high speed railway tunnels
by: Zeping Yang, et al.
Published: (2025-07-01) -
Characteristics and Deformation Mechanisms of Neogene Red-Bed Soft Rock Tunnel Surrounding Rock: Insights from Field Monitoring and Experimental Analysis
by: Jin Wu, et al.
Published: (2025-05-01) -
Numerical Study on Hydraulic Coupling and Surrounding Rock Deformation for Tunnel Excavation Beneath Reservoirs
by: Shaodan Wang, et al.
Published: (2025-05-01)