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China Tunnel Technology: Dynamic prediction and multi-objective optimization on driving position of tunnel boring machine (TBM): an automated deep learning approach
Dynamic prediction and multi-objective optimization on driving position of tunnel boring machine (TBM): an automated deep learning approach
Yue Pan a, Ziyi Wang a, Lin Sun b & Jin-Jian Chen a
a Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, Department of Civil Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
b Shanghai Mechanized Construction Group, 701 Luochuan Road, Shanghai, 200072, China
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https://link.springer.com/article/10.1007/s11440-024-02271-6
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https://link.springer.com/article/10.1007/s11440-024-02271-6
Dynamic prediction and multi-objective optimization on driving position of tunnel boring machine (TBM): an automated deep learning approach
link.springer.comActa Geotechnica - This paper proposes an automated deep learning (AutoDL) framework for dynamic prediction and multi-objective optimization (MOO) on the driving position of the tunnel boring...