Data-driven real-time prediction for attitude and position of super-large diameter shield using a hybrid deep learning approach
The presented research introduces a novel hybrid deep learning approach for the dynamic prediction of the attitude and position of super-large diameter shields - a critical consideration for construction safety and tunnel lining quality. This study proposes a hybrid deep learning approach for predic...
Main Authors: | Yanbin Fu, Lei Chen, Hao Xiong, Xiangsheng Chen, Andian Lu, Yi Zeng, Beiling Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
KeAi Communications Co., Ltd.
2024-04-01
|
Series: | Underground Space |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2467967423001332 |
Similar Items
-
Development and consideration of Chinese super-large diameter shield tunnel
by: Wei Qiu, et al.
Published: (2024-03-01) -
Numerical Investigation on the Influence of Super-Large-Diameter Shield Tunneling on Nearby Existing Metro Tunnels and the Protection Scheme
by: Yixiang Li, et al.
Published: (2023-12-01) -
Research on Stress Characteristics of Segment Structure during the Construction of the Large-Diameter Shield Tunnel and Cross-Passage
by: Zhongsheng Tan, et al.
Published: (2020-07-01) -
Response of operating metro tunnels to compensation grouting of an underlying large-diameter shield tunnel: A case study in Hangzhou
by: Xiaolu Gan, et al.
Published: (2022-04-01) -
Risks analysis of large diameter slurry shield tunneling in urban area
by: Yi Zeng, et al.
Published: (2023-12-01)