关键词: 病害发展分析, 越江盾构隧道, 病害预测, SHAP, 随机森林

Abstract: Rail transit construction technology in China is becoming more and more mature, however, the current situation of tunnel deformation in a water-rich environment can not be changed. In the field of engineering, scholars have conducted in-depth research on the causes, influencing factors, control and treatment of tunnel diseases. However, there are few studies on the disease distribution and development prediction of tunnels, especially cross-river shield tunnels. In order to make up for the blank in the field of disease development prediction of cross-river shield tunnels, the study forecasts the next phase of monitoring data based on RF added SHAP values and historical monitoring data which are from the full-section scanning of the shield tunnel in the cross-river section by 3D laser measurement technology. After evaluating the accuracy of the prediction results, we can analyze the prediction data to determine the location and degree of the tunnel deformation, which will provide the basis for subway operation and maintenance.

Key words: disease development analysis, cross-river shield tunnel, disease forecast, SHAP, random forest