基于优化神经网络的圆形隧道受剪变形分析  

Analysis on Shear Deformation in a Circular Tunnel Based on Optimized Neural Network

作　　者：黄迪文 霍宏斌 陈东[1] HUANG Diwen;HUO Hongbin;CHEN Dong(Faculty School of Engineering,China University of Geosciences,Wuhan 430074)

机构地区：[1]中国地质大学(武汉)工程学院,武汉430074

出　　处：《现代隧道技术》2021年第6期102-110,共9页Modern Tunnelling Technology

摘　　要：圆形隧道在地震横波的冲击作用下易发生椭圆变形,评估其变形量的主要方法有解析解法和数值模拟法,鉴于此,文章提出了一种基于优化神经网络的新方法,通过构建的算法模型准确预测椭圆变形量。文章先采用思维进化算法(MEA)优化的反向传播神经网络(BPNN)确定圆形隧道衬砌的椭圆变形量ΔD,从既有文献资料和数值分析中收集了一个包含370组数据集的样本库,数值分析符合现有解析解的假设,文献资料收集的数据包含了工程现场量测的结果。由于界面强度R_(inter)和埋深h是大多数解析解都没有考虑到的,因此将其作为额外的输入参数引入。三个统计性能指标R^(2)、MAPE和RMSE的预测结果表明,改进后的BPNN具有良好的泛化性能。文章最后探讨了在训练后的网络中使用平均影响值(MIV)算法进行参数影响分析,计算结果反映了各项输入参数和输出参数之间的相关性强弱,预测结果与解析解和数值分析结果的契合度高。A circular tunnel is prone to elliptical deformation under the impact of seismic shear wave.Main methods for evaluating the deformation are analytical solution and numerical simulation.So,in this paper,a new method based on optimized neural network is proposed to accurately predict the elliptical deformation through the constructed algorithm model.In the first part of this paper,the back propagation neural network(BPNN)optimized by mind evolutionary algorithm(MEA)is adopted to determine the elliptical deformationΔD of the circular tunnel lining.Then,a sample database containing 370 data sets is collected from the existing literatures and numerical analysis examples.The numerical analysis is in line with the assumption of the existing analytical solutions,and the data collected from the literatures include the measured results on the site.Since not considered in most analytical solutions,the interface strength Rinter and buried depth h are introduced as additional input parameters.The values of three statistical performance indexes R2,MAPE and RMSE indicate that the improved BPNN has good generalization performance.In the second part,the mean impact value(MIV)algorithm is used to analyze the impact of parameters in the trained network.The calculation results reflect the correlation between input parameters and output ones,and the prediction results are in good agreement with that of analytical solutions and numerical analysis.

关 键 词：圆形隧道 椭圆化变形 地震横波 参数分析 优化神经网络 

分 类 号：U451.4[建筑科学—桥梁与隧道工程]