Research on Soil Pressure Prediction of Shield Tunneling Machine Based on Multi-Intelligent Algorithm Fusion
A strategy based on advanced prediction model framework is proposed to achieve accurate prediction of soil pressure during shield tunneling process.The goal of this strategy is to provide support for soil pressure balance control by accurately predicting soil pressure.The prediction process mainly consists of two steps.Firstly,discrete wavelet transform(DWT)and one-dimensional convolutional neural network(1DCNN)are used to preprocess and extract features from the original data.Secondly,using long-short term memory neural networks(LSTM)to accurately predict changes in soil pressure.This strategy aims to accurately track future changes in soil pressure,providing scientific basis for maintaining soil pressure balance inside and outside the sealed chamber during shield tunneling,and improving the safety and efficiency of shield tunneling.
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