在预测隧道围岩变形的过程中,运用神经网络的方法,建立非线性的预测模型,结合张涿高速公路林里隧道的变形实测数据,借助MATLAB 7.1平台,模拟了隧道围岩的变形过程;实验结果表明:RBF神经网络方法在隧道围岩变形的预测中,具有运算速度快,预测精度高,模型稳定可靠的特点,在隧道施工过程中,能够有效的辅助施工控制,提供预测报告。 In the process of predicting the deformation of surrounding rock of tunnel, a nonlinear prediction model is established by neural network method. Combined with the measured data of deformation in Linli Tunnel of Zhangjiu Expressway, the deformation process of surrounding rock is simulated with MATLAB 7.1. The experimental results show that the RBF neural network method has the advantages of fast calculation speed, high prediction accuracy and stable and reliable model in the prediction of tunnel surrounding rock deformation. It can effectively assist construction control and provide forecasting reports during the tunnel construction.