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On-line Access: 2024-01-15

Received: 2023-01-07

Revision Accepted: 2023-08-07

Crosschecked: 2024-01-15

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Citations:  Bibtex RefMan EndNote GB/T7714


Xiaowei YE


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Journal of Zhejiang University SCIENCE A 2024 Vol.25 No.1 P.1-17


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

Author(s):  Xiaowei YE, Xiaolong ZHANG, Yanbo CHEN, Yujun WEI, Yang DING

Affiliation(s):  MOE Key Laboratory of Soft Soils and Geoenvironmental Engineering, Zhejiang University, Hangzhou 310058, China; more

Corresponding email(s):   chenyanbo@zju.edu.cn

Key Words:  Random forest (RF), Particle swarm optimization (PSO), Upward displacement of lining, Machine learning prediction, Shield tunneling construction

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Xiaowei YE, Xiaolong ZHANG, Yanbo CHEN, Yujun WEI, Yang DING. Prediction of maximum upward displacement of shield tunnel linings during construction using particle swarm optimization-random forest algorithm[J]. Journal of Zhejiang University Science A, 2024, 25(1): 1-17.

@article{title="Prediction of maximum upward displacement of shield tunnel linings during construction using particle swarm optimization-random forest algorithm",
author="Xiaowei YE, Xiaolong ZHANG, Yanbo CHEN, Yujun WEI, Yang DING",
journal="Journal of Zhejiang University Science A",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T Prediction of maximum upward displacement of shield tunnel linings during construction using particle swarm optimization-random forest algorithm
%A Xiaowei YE
%A Xiaolong ZHANG
%A Yanbo CHEN
%A Yujun WEI
%A Yang DING
%J Journal of Zhejiang University SCIENCE A
%V 25
%N 1
%P 1-17
%@ 1673-565X
%D 2024
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2300011

T1 - Prediction of maximum upward displacement of shield tunnel linings during construction using particle swarm optimization-random forest algorithm
A1 - Xiaowei YE
A1 - Xiaolong ZHANG
A1 - Yanbo CHEN
A1 - Yujun WEI
A1 - Yang DING
J0 - Journal of Zhejiang University Science A
VL - 25
IS - 1
SP - 1
EP - 17
%@ 1673-565X
Y1 - 2024
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2300011

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 (R2=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.


结论:1.提出的PSO-RF混合模型明显提升了管片最大上浮量预测模型的预测性能;2. PSO-RF管片上浮预测模型成功预测了管片的最大上浮量,有更小的预测误差(MAE=4.04mm,RMSE=5.67mm)与更高的相关性(R2=0.915);3.盾构机千斤顶推力与隧道埋深是影响管片最大上浮量预测模型性能的主要因素。


Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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