Abstract: To avoid consequences caused by the unbalance of earth pressure of the in-chamber of earth pressure balance(EPB) shields, such as instability of tunnel face, the loss of stratum and surface settlement, the GA algorithm was embedded into the PSO algorithm for parameter optimization, and a prediction model of chamber earth pressure based on grey least squares support vector machine was established combined with grey theory, which was verified by an actual project.Research indicates that the GA-PSO-GLSSVM chamber earth pressure prediction model takes six driving parameters as input set, including total thrust, cutter torque, propulsion speed, screw speed, screw torque and grouting amount, and comprehensively considers the interaction between shield driving parameters, making the prediction model more realistic.The prediction model integrates the global search ability of the GA algorithm, the fast convergence of the PSO algorithm and the anti-disturbance ability of the GM model, so improves the prediction accuracy of EPB chamber earth pressure in complex strata.Compared with the prediction results of other prediction models, the root mean square error(RMSE),mean absolute error(MAE),mean absolute percentage error(MAPE) and determination coefficient(R2) of the GA-PSO-GLSSVM model is significantly better.The prediction results have higher goodness of fit and accuracy, and have significant applicability to the prediction of EPB shield chamber earth pressure in sand and pebble complex strata.The research results can provide a reference for EPB shield tunneling parameter control in the sandy pebble stratum.