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Bayesian deep reinforcement learning for uncertainty quantification and adaptive support optimization in deep foundation pit engineering

Abstract This study develops a novel framework integrating Bayesian inference with deep reinforcement learning for uncertainty quantification and adaptive support optimization in multi-physics coupled deep foundation pit systems. The methodology systematically incorporates prior knowledge and real-t...

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Κύριος συγγραφέας:	Weiming Gu
Μορφή:	Artigo
Γλώσσα:	Inglês
Έκδοση:	Nature Portfolio 2025-10-01
Σειρά:	Scientific Reports
Θέματα:	Deep foundation pit Bayesian inference Deep reinforcement learning Uncertainty quantification Multi-physics coupling Adaptive optimization
Διαθέσιμο Online:	https://doi.org/10.1038/s41598-025-19002-w
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Bayesian deep reinforcement learning for uncertainty quantification and adaptive support optimization in deep foundation pit engineering

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