期刊
AUTOMATION IN CONSTRUCTION
卷 147, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.autcon.2022.104732
关键词
Shield machine; Ground surface settlement; Spatial -temporal fusion mechanism; 3D residual unit structure; STF-Network
The maximum ground surface settlement prediction is a complex problem with many influencing factors. A hybrid prediction dataset is constructed to estimate the settlement, which includes geological and construction parameters based on spatial and temporal series. A spatial-temporal fusion network (STF-Network) is proposed to handle the multi-modal and multi-variate series prediction task.
The maximum ground surface settlement prediction is a complex problem as the settlement depends on plenty of intrinsic and extrinsic factors. To obtain the approximate range of the settlement, a hybrid prediction dataset including the geological and construction parameters is built using spatial and temporal series according to the sampling methods. The settlement prediction task is transformed into a multi-modal and multi-variate series prediction task. Hence, a spatial-temporal fusion network (STF-Network) is proposed. The spatial-temporal fusion mechanism is firstly designed to establish the spatial-temporal fusion map, which makes spatial and temporal series interact earlier. Then, the 3D residual unit structure is designed to capture the features of temporal series and spatial-temporal fusion map, and two fully-connected layers are established to capture the spatial structural information. Finally, the final output is merged by the three components. The experimental results for STF-Network demonstrate the superiority over state-of-the-art methods.
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