Abstract:To achieve accurate prediction of settlement during tunnel construction, this study proposes a prediction method for settlement in construction tunnels through neural networks based on spatiotemporal feature region. This method effectively integrates multi-dimensional spatial characteristics and makes a reasonable prediction of the future evolution trend according to the current tunnel ground settlement. Taking the ground observation data at the Luanchuan end of Baijiazhuang Tunnel as an example, this study analyzes the prediction performance of the proposed method. The prediction results show that the sensing data of tunnel ground settlement is accurate and robust. The research can be applied to the monitoring and management process of actual tunnel construction.