Research Article
A Novel Intelligent Method for Predicting the Penetration Rate of the Tunnel Boring Machine in Rocks
Table 1
Review of several TBM performance prediction models using the dataset from the Queens Water Tunnel .
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Nomenclature in this table: brittleness index (BI); Brazilian tensile strength (BTS); classification and regression tree (CART); cutterhead power (CP); cutterhead torque (CT); differential evolution (DE); Dubois–Prade decision operator (DPDO); distance between planes of weakness (DPW); extended multifactorial fuzzy evaluation (EMFE); field penetration index (FPI); gene expression programming (GEP); grey wolf optimizer (GWO); hybrid harmony search (HS-BFGS); imperialist competitive algorithm (ICA); individual cutter force (FN); mean absolute percentage error (MAPE); mean relative error (MRE); mean squared error (MSE); penetration rate (PR); peak slope index (PSI); coefficient of correlation (R2); root mean square error (RMSE); rock quality designation (RQD); coefficient of the cross correlation (r); statistical analysis (SA); specific energy (SE); the spacing between the weakness planes (SWP); thrust force (TF); uniaxial compressive strength of intact rock (UCS); variance accounted for (VAF); angle between the longitudinal tunnel axis and the plane of weakness (α). |