Prediction of maximum upward displacement of shield tunnel linings during construction using particle swarm optimization-random forest algorithm

During construction, the shield linings of tunnels often face the problem of local or overall upward movement after leaving the shield tail in soft soil areas or during some large diameter shield projects. Differential floating will increase the initial stress on the segments and bolts which is harm...

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Bibliographic Details
Published in:Journal of Zhejiang University. A. Science 2024, Vol.25 (1), p.1-17
Main Authors: Ye, Xiaowei, Zhang, Xiaolong, Chen, Yanbo, Wei, Yujun, Ding, Yang
Format: Article
Language:English
Subjects:
Algorithms
Civil Engineering
Classical and Continuum Physics
Engineering
Excavation
Industrial Chemistry/Chemical Engineering
Initial stresses
Mechanical Engineering
Particle swarm optimization
Prediction models
Research Article
Root-mean-square errors
Tunnel construction
Tunnel linings
Tunneling shields
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Summary:During construction, the shield linings of tunnels often face the problem of local or overall upward movement after leaving the shield tail in soft soil areas or during some large diameter shield projects. Differential floating will increase the initial stress on the segments and bolts which is harmful to the service performance of the tunnel. In this study we used a random forest (RF) algorithm combined particle swarm optimization (PSO) and 5-fold cross-validation (5-fold CV) to predict the maximum upward displacement of tunnel linings induced by shield tunnel excavation. The mechanism and factors causing upward movement of the tunnel lining are comprehensively summarized. Twelve input variables were selected according to results from analysis of influencing factors. The prediction performance of two models, PSO-RF and RF (default) were compared. The Gini value was obtained to represent the relative importance of the influencing factors to the upward displacement of linings. The PSO-RF model successfully predicted the maximum upward displacement of the tunnel linings with a low error (mean absolute error (MAE)=4.04 mm, root mean square error (RMSE)=5.67 mm) and high correlation ( R 2 =0.915). The thrust and depth of the tunnel were the most important factors in the prediction model influencing the upward displacement of the tunnel linings.
ISSN:1673-565X
1862-1775
DOI:10.1631/jzus.A2300011