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隧道建设(中英文) ›› 2012, Vol. 32 ›› Issue (2): 175-179.DOI: 10.3973/j.issn.1672-741X.2012.02.009

• 研究与探索 • 上一篇    下一篇

基于神经网络的大断面软土隧道收敛安全监测的预测方法

郝飞,孙全胜, 周晓杰   

  1. (东北林业大学, 哈尔滨 150040)
  • 收稿日期:2011-11-14 修回日期:2012-02-27 出版日期:2012-04-20 发布日期:2012-05-03
  • 作者简介:郝飞(1986—),男,河北张家口人,东北林业大学在读硕士,从事桥梁与隧道方面的研究工作。

Prediction of Convergence of Large Crosssection Soft Soil Tunnels Based on Neural Network

HAO Fei, SUN Quansheng, ZHOU Xiaojie   

  1. (Northeast Forestry University, Harbin 150040, China)
  • Received:2011-11-14 Revised:2012-02-27 Online:2012-04-20 Published:2012-05-03

摘要: 在软土隧道的施工工程中,隧道的收敛变形是一个十分复杂的过程,影响因素很多,为了能够合理地模拟隧道施工后的收敛变形,指导隧道的安全施工,采用BP神经网络方法以时间和里程2个方面为出发点,对软土隧道的收敛变形进行预测。以哈尔滨市保健路打通工程为实例,证明了利用BP网络的预测结果能够很好地指导软土隧道的施工,精度更准确,对实际工程有更好地指导意义。

关键词: 大断面软土隧道, 收敛, 神经网络, 预测方法

Abstract: The convergence of soft soil tunnels is very complex. In the paper, the convergence of soft soil tunnels is predicted by means of BP neural network method, with the construction of the tunnel on Baojian Road in Harbin as an example, so as to simulate the convergence of soft soil tunnels and to provide guidance for the safe construction of soft soil tunnels. The practice proves that the results of prediction by BP neural network are accurate and can provide guidance for the construction of soft soil tunnels.

Key words: large crosssection soft soil tunnel, convergence, neural network, prediction method