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Intelligent Dynamic Control of Shield Parameters Using a Hybrid Algorithm and Digital Twin Platform

AUTOMATION IN CONSTRUCTION(2025)

Huazhong Univ Sci & Technol | Hong Kong Polytech Univ | Wuhan Univ

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Abstract
This paper presents a digital twin (DT) platform integrated with an online optimization algorithm that combines Bayesian Optimization (BO), Categorical Boosting (CatBoost), and the Nondominated Sorting Genetic Algorithm (NSGA)-III. The platform enables multi-objective dynamic optimization of shield parameters under varying geological conditions. Using the Wuhan Metro as a case study, the effectiveness of the method is validated. The results demonstrate that: (1) the DT model accurately estimates shield machine performance, with an R2 of no less than 0.957 on the test set across three geological conditions; (2) the online optimization significantly enhances shield machine performance, with a comprehensive optimization improvement of over 25 % across all conditions; (3) comparison of the constructed algorithm's accuracy, along with Shapley additive explanations, confirms the accuracy, interpretability, and universality of the proposed algorithm.
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Key words
Shield construction,Shield construction parameters,Digital twin,Intelligent prediction,Multiobjective optimization control,BO-CatBoost-NSGA-III,SHapley Additive exPlanations
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