基于遗传算法的BP神经网络在隧道围岩参数反演和变形预测中的应用

摘要

隧道变形的准确预测需要以可靠的围岩力学参数为前提.文章通过构建基于遗传算法的BP神经网络智能反分析系统(GA-BP),实现了遗传算法自动搜索BP网络参数,大大提高了反演分析的效率,并将构建的GA-BP智能反分析系统应用到下穿沈丹高速公路的大顶山隧道围岩参数反演和变形预测中.分析结果表明,GA-BP反分析系统收敛速度较快,围岩参数反演和变形预测较为准确.%Reliable mechanical parameters of surrounding rock are imperative for the accurate prediction of tunnel deformation.A GA-BP based neural network back analysis system is proposed and automatic searching for BP net-work parameters can be realized,with the efficiency of inversion analysis increasing greatly.This GA-BP intelligent back analysis system is applied to the inversion of rock mass parameters and deformation prediction for the Dading-shan tunnel passing underneath the Shenyang-Dandong expressway.The results show that the convergence speed of the GA-BP back analysis system is fast and the parameter inversion of the surrounding rock and deformation predic-tion is accurate.