Shield tunneling efficiency and stability enhancement based on interpretable machine learning and multi-objective optimization

Shield tunneling efficiency and stability enhancement based on interpretable machine learning and multi-objective optimization

Adequate control of shield machine parameters to ensure the safety and efficiency of shield construction is a difficult and complex problem. To address this problem, this paper proposes a hybrid intelligent optimization framework that combines interpretable machine learning, intelligent optimization...

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Bibliographic Details
Main Authors: Wenli Liu, Yang Chen, Tianxiang Liu, Wen Liu, Jue Li, Yangyang Chen
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-06-01
Series:Underground Space
Subjects:
Shield tunnelling machine
Interpretable machine learning
Hyperparameter optimization
Multi-objective optimization
Field penetration index
Ground settlement
Online Access:http://www.sciencedirect.com/science/article/pii/S2467967425000200
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http://www.sciencedirect.com/science/article/pii/S2467967425000200

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