Dynamic prediction and optimization of tunneling parameters with high reliability based on a hybrid intelligent algorithm

In this paper, a hybrid intelligent framework comprising Bayesian optimization (BO), gradient boosting with categorical features (CatBoost) and the nondominated sorting genetic algorithm-III (NSGA-III) was proposed to support multiobjective optimization of shield construction parameters without large sample datasets, improve the shield performance, and ensure reliable and interpretable results. First, with the use of the specific tunneling energy, advancing speed and cutter wear as objective functions, a BO-CatBoost prediction model for shield construction parameters and various objectives was constructed, and the key influencing factors were identified via the SHapley Additive exPlanations (SHAP) method. Then, a BO-CatBoost-NSGA-III model was developed to obtain Pareto solutions under different scenarios involving the adjustment of the key influencing factors. Finally, adopting the Wuhan Metro as the background, the accuracy, stability, and generalizability of the constructed algorithm were verified. The results indicated that (1) the developed BO-CatBoost algorithm is superior to 9 other algorithms. The R² values of the proposed approach were 0.976 and 0.901–0.976 on the test set. (2) The developed BO-CatBoost-NSGA-III algorithm could be used to obtain Pareto solutions under different scenarios via the adjustment of the key influencing factors with the SHAP method, and the optimal solutions could facilitate improvements in the advancing speed, specific tunneling energy and cutter wear of 3.45 %, 6.09 %, and 0.52 %, respectively, with an overall average reliability of 90.5 %. (3) By comparing various prediction algorithms, optimization schemes of different objectives and geological conditions, the accuracy, stability, and generalizability of the constructed algorithm were verified. The developed BO-CatBoost-NSGA-III framework could enable dynamic adjustment of shield construction parameters for decision-making purposes in the event of conflicting shield construction objectives and exhibits generality.