堡镇隧道围岩变形的神经网络预测

Prediction of Surrounding Rock Deformation with Nerve Network in Baozhen Tunnel

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经济合理性的重要指标。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。针对宜万铁路堡镇隧道软弱围岩区段施工大变形特点,采用神经网络技术对其变形量进行了预测分析,预测结果经过工程实践检验,具有相对较高的准确性和可靠性,为隧道施工决策提供了有效依据。

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 measurement time sequence, so we can set up some effective models and methods to predict the surrounding rock deformation. According to the large deformation characteristics of the soft surrounding rock in Baozhen tunnel of Yiwan railway, the nerve network technology is adopted to predict the subsidence displacements. The predicting results is almost accurate, which provides effectual gist for tunnel construction.