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Hybrid deep learning approach for rock tunnel deformation prediction based on spatio-temporal patterns

Junfeng Sun Yong Fang Hu Luo Zhigang Yao Long Xiang Jianfeng Wang Yubo Wang Yifan Jiang

地下空间（英文）2025，Vol.20Issue(2)：100-118,19.

地下空间（英文）2025，Vol.20Issue(2)：100-118,19.DOI:10.1016/j.undsp.2024.04.008

Hybrid deep learning approach for rock tunnel deformation prediction based on spatio-temporal patterns

Junfeng Sun ¹Yong Fang ¹Hu Luo ¹Zhigang Yao ¹Long Xiang ²Jianfeng Wang ¹Yubo Wang ¹Yifan Jiang¹

作者信息

1. State Key Laboratory of Intelligent Geotechnics and Tunnelling,Southwest Jiaotong University,Chengdu 610031,China
2. Sichuan Highway Planning,Survey,Design and Research Institute,Chengdu 610041,China
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摘要

关键词

GAT-LSTM/Deep learning/Transfer learning/Tunnel deformation

Key words

GAT-LSTM/Deep learning/Transfer learning/Tunnel deformation

引用本文复制引用

Junfeng Sun,Yong Fang,Hu Luo,Zhigang Yao,Long Xiang,Jianfeng Wang,Yubo Wang,Yifan Jiang..Hybrid deep learning approach for rock tunnel deformation prediction based on spatio-temporal patterns[J].地下空间（英文）,2025,20(2):100-118,19.

基金项目

This work was financially supported by the Sichuan Pro-vince Natural Science Foundation Innovative Research Group Project(Grant No.2024NSFTD0013). （Grant No.2024NSFTD0013）

地下空间（英文）

ISSN：2096-2754

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