【摘要】 隧道新奥法施工中,常以围岩变形量作为评判围岩稳定性和支护结构合理性的重要指标.公路隧道围岩变形量是随时间而变化的数据序列,因而可以建立一些实时跟踪预测模型和方法.本文根据阳宗隧道围岩拱顶下沉位移变形的特性,采用神经网络技术来预测其变形量,结果表明该方法简易、有效.更多还原

【Abstract】 The surrounding rock deformation of highway tunnel is an important index to assess its stability and economy of support structure in NATM.It is a data column which is related with measuremet time sequence,so we can set up some effective models and methods to predicate the surrounding rock deformation.According to the surrounding rock deformation characteristics of Yangzong highway tunnel,this paper adopts the nerve network technology to predict the subsidence displacements.The research results show this prediction method is simple and effective.更多还原