Real-time analysis and regulation of EPB shield steering using Random Forest

Settlement control is an essential part of the tunnel construction process. This paper proposes two novel computational models based on the Random Forest (RF) algorithm for supporting automatically steering Earth Pressure Balanced (EPB) shield. The first model is utilized for predicting tunneling-induced settlement and the other estimates shield operational parameters. A PSO-RF hybrid algorithm which intergrates the Particle Swarm Optimization (PSO) and the RF algorithms is proposed to optimize shield operational parameters when the settlement exceeds the tolerated value. The proposed models are adopted in the case study of Changsha Metro Line 4 project. The results indicate that the predicted settlements show great agreement with the measured settlements. The face pressure and grout filling are the most significant shield operational parameters to control the settlement as a result of Global Sensitivity Analysis (GSA). The anomalous settlement (≥10 mm) can be controlled under tolerated value after the face pressure and grout filling values are optimized by the PSO-RF hybrid algorithm. Simultaneously, the consistency of the face pressure and grout filling values calculated by the PSO-RF and the grid search method demonstrates the feasibility and applicability of proposed hybrid algorithm. •Random forest models are established for predicting tunneling-induced settlement and shield operational parameters.•A hybrid algorithm is proposed for optimizing shield operational parameters.•Combining settlement and operational parameters prediction models achieves the automatic control of shield machine.