基于MK-LSTM算法的盾构掘进参数相关性分析及结构变形预测

doi:10.13229/j.cnki.jdxbgxb.20220975

Abstract

Abstract:

MIC-K-median-LSTM（MK-LSTM）algorithm was proposed to analyze the correlation of parameters and predict the structural deformation. Firstly， the improved MIC algorithm is developed to analyze the correlation between the different input parameters and structural deformation， then to preprocess the input parameters based on their correlation coefficients. The prediction accuracy and efficiency using different dimensions of input parameters are analyzed through the LSTM model and the optimal input parameter dimensions are selected. The results show that： The influence of the shield parameters on the existing structural deformation is larger than soil parameters； The MK algorithm can effectively reduce the computational complexity and the impact of noise in raw data and the data pre-process is beneficial to improve prediction accuracy； MK-LSTM algorithm can effectively predict the deformation law of the structure over time， considering the effect of the data dimension on the improvement of the prediction accuracy and the influence of the calculation efficiency， dimension pruning can be adopted in the actual engineering based on the parameter correlation.

Key words: shield tunnelling, machine learning, parameter dimension, parameter correlation, deformation

CLC Number:

TU472

Cheng CHEN,Pei-xin SHI,Peng-jiao JIA,Man-man DONG. Correlation analysis of shield driving parameters and structural deformation prediction based on MK-LSTM algorithm[J].Journal of Jilin University(Engineering and Technology Edition), 2024, 54(6): 1624-1633.

Figures/Tables 13

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方案	输入参数
1	T 、R 、N 、P₄ 、V、 P₂、c、φ、 P₃ 、G 、P₁ 、F
2	T 、R 、N 、P₄ 、V、 P₂、c、φ、 P₃ 、G 、P₁
3	T 、R 、N 、P₄ 、V、 P₂、c、φ、 P₃ 、G
4	T 、R 、N 、P₄ 、V、 P₂、c、φ、 P₃
5	T 、R 、N 、P₄ 、V、 P₂、c、φ
6	T 、R 、N 、P₄ 、V、 P₂、c
7	T 、R 、N 、P₄ 、V、 P₂
8	T 、R 、N 、P₄ 、V
9	T 、R 、N 、P₄
10	T 、R 、N
11	T 、R

指标	方案1	方案2	方案3	方案4	方案5	方案6	方案7	方案8	方案9	方案10	方案11
MAE	0.111	0.144	0.157	0.179	0.189	0.231	0.274	0.299	0.354	0.421	0.654
RMSE	0.112	0.131	0.164	0.189	0.202	0.254	0.297	0.342	0.417	0.528	0.749
R²	0.977	0.946	0.934	0.922	0.903	0.872	0.846	0.802	0.763	0.721	0.618

Correlation analysis of shield driving parameters and structural deformation prediction based on MK-LSTM algorithm

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