Intelligent real-time prediction of multi-region thrust of EPB shield machine based on SSA-LSTM

Abstract During the tunneling process of shield machine, accurate determination parameters is guarantee safe operation machine. Through real-time construction data analysis and mining at next moment are obtained in real-time. Based on this, this paper proposes an intelligent prediction method for multi-region thrust EPB machine based Sparrow Search algorithm-Long Short-term Memory (SSA-LSTM). By correlation big data, features with a great obtained. And it used as input LSTM model to explore nonlinear relationship between inputs output. SSA optimize establish more relationship, then accurately The simulation results show that SSA-LSTM can predict each region moment, performance better than other models. provides reference basis implement regulation effective control Earth pressure balance (EPB) sealed cabin ensure safety, which has engineering application value.