Building Information Modeling Driven By Spatio-Temporal Swin-U-Net: Ultra-short-term Deformation Prediction of Adjacent Municipal Pipelines During Deep Subway Station Excavation
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https://figshare.com/articles/dataset/Building_Information_Modeling_Driven_By_Spatio-Temporal_Swin-U-Net_Ultra-short-term_Deformation_Prediction_of_Adjacent_Municipal_Pipelines_During_Deep_Subway_Station_Excavation/31225822
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The excavation of deep subway station foundation pits in densely built urban areas poses considerable risks to adjacent municipal pipelines, where deformation may evolve rapidly under complex and time-varying construction conditions. Existing statistical models often fail to capture nonlinear spatiotemporal deformation patterns, while numerical simulation approaches are computationally expensive and difficult to deploy for ultra-short-term, high-frequency prediction required on construction sites. Moreover, current applications of Building Information Modeling (BIM) are largely limited to static visualization and lack effective integration with real-time monitoring data.
创建时间:
2026-02-02



