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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。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。根据通渝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
In the construction of tunnels during the new Austrian law, the deformation of surrounding rock is often used as an important index to evaluate the stability of surrounding rock and the economic rationality of supporting structure. The deformation of surrounding rock mass of highway tunnel is a data sequence changing with time, so some real-time tracking prediction models and methods can be established. According to the characteristics of displacement deformation of surrounding rock vault of Tongyu Tunnel, neural network technology was used to predict the deformation, the results show that the method is simple and effective