Water leakage classification of expressway operationa tunnel based on BP neural network

被引：0
|
作者：
Zou, Yulin [1 ]
He, Chuan [1 ]
Zhou, Yi [1 ]
Yao, Chaofan [1 ]
Zhang, Zheng [1 ]
机构：
[1] Southwest Jiaotong Univ, MOE Key Lab Transportat Tunnel Engn, Chengdu 610031, Peoples R China
来源：
PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ELECTRONIC & MECHANICAL ENGINEERING AND INFORMATION TECHNOLOGY (EMEIT-2012) | 2012年 / 23卷
关键词：
tunnel engineering; grade evaluation model; BP neural network; leakage tunnel; operational tunnel;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, factors influencing the tunnel leakage are analyzed synthetically, based on present situations of water leakage of operational highway tunnel in Chongqing area. Standard of tunnel leakage grade is determined and index system of tunnel leakage model is established by choosing physical geography, surrounding rock, underground water, lining and drainage facilities as the first grade indexes and choosing 12 factors such as vegetation, annual precipitation, and tunnel depth as the second indexes. Xiu-shan tunnel and Zheng-yang tunnel are selected as evaluation model of training sample from 66 operational tunnels in Chongqing area. The results are the consistent in comparing the neural network evaluation and manual evaluation. It is shown that this model has good applicability in grade evaluation of tunnel leakage, and classification of tunnel leakage could be done quickly and accurately.
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页数：4
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