A data-driven spatial-temporal model for prediction of tunnel deformation
Predicting deformation trends in tunnels is crucial for structural damage diagnosis and accident prevention. Due to the deficiency of incomplete influencing factors and rough prediction accuracy, this paper proposes a data-driven spatial-temporal model to predict tunnel deformation behavior. Conside...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Maximum Academic Press
2025-03-01
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| Series: | Digital Transportation and Safety |
| Subjects: | |
| Online Access: | https://www.maxapress.com/article/doi/10.48130/dts-0025-0003 |
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