Inversion Analysis of Tunnel Surrounding Rock Parameters Based on BP Neural Network
Based on the project of East Taiping Mountain Tunnel in Zhangjiakou City,a finite element model with MIDAS software was established.GA-BP neural network by use of annealing algorithm was optimized,and then orthogonal test and construct GASA-BP neural network to was designed.According to the values of simulations of tunnel arch roof settlement,horizontal convergence and invert arch uplift,the inversion analysis on elastic modulus,cohesive strength and internal friction angle of the surrounding rock were carried out.The results show that,for the value of simulation of tunnel arch roof settlement,horizontal convergence and invert uplift,which is obtained from the inversion by use of GASA-BP neural network,and the value of the actual monitoring,the maximum difference between them are 6.60％,19.80％and 2.16％,respectively.Compared with BP neural network,GASA-BP neural network can provide higher accuracy of inversion,and the precision of surrounding rock parameters obtained by the inversion is within a reasonable range.The finite element model established under these parameters can contribute to good simulation of engineering practice.
tunnellingbroken rockneural networkannealing algorithminversion analysisorthogonal testsettlement monitoringparameter of surrounding rock
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