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.
引用
收藏
页数:4
相关论文
共 50 条
  • [41] The Comparison of Spectral Classification Based on DBN, BP Neural Network and SVM
    Li Jun-feng
    Wang Yue-le
    Hu Sheng
    He Hui-ling
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36 (10) : 3261 - 3264
  • [43] Study on Classification for Remote Sensing Image based on BP Neural Network
    Wang Chongchang
    Zhang Jianping
    PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9, 2009, : 2187 - 2190
  • [44] Classification of High Quality Carbon Steel Based on BP Neural Network
    Liu, Lanlan
    Zhang, Taohong
    Xie, Yonghong
    Li, Li
    Zhang, Dezheng
    Wulamu, Aziguli
    EIGHTH CHINA NATIONAL CONFERENCE ON FUNCTIONAL MATERIALS AND APPLICATIONS, 2014, 873 : 54 - 59
  • [45] An optimized classification algorithm by BP neural network based on PLS and HCA
    Weikuan Jia
    Dean Zhao
    Tian Shen
    Shifei Ding
    Yuyan Zhao
    Chanli Hu
    Applied Intelligence, 2015, 43 : 176 - 191
  • [46] An optimized classification algorithm by BP neural network based on PLS and HCA
    Jia, Weikuan
    Zhao, Dean
    Shen, Tian
    Ding, Shifei
    Zhao, Yuyan
    Hu, Chanli
    APPLIED INTELLIGENCE, 2015, 43 (01) : 176 - 191
  • [47] Classification of flour types based on PSO-BP neural network
    Chen, Maomao
    Liu, Mingliang
    PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC), 2018, : 2591 - 2595
  • [48] Image Classification Based on BP Neural Network and Sine Cosine Algorithm
    Song, Haoqiu
    Ye, Zhiwei
    Wang, Chunzhi
    Yan, Lingyu
    PROCEEDINGS OF THE 2019 10TH IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS - TECHNOLOGY AND APPLICATIONS (IDAACS), VOL. 1, 2019, : 562 - 566
  • [49] Classification of Car Scratch Types Based on Optimized BP Neural Network
    Zhang, Xing
    Zhou, Liang
    CLOUD COMPUTING AND SECURITY, PT V, 2018, 11067 : 148 - 158
  • [50] Research on Target Polarization Recognition and Classification Based on BP Neural Network
    Wu, Bang
    Jia, Qi
    Xu, Wei-dong
    Lv, Xu-liang
    Hu, Jiang-hua
    PROCEEDINGS OF THE 2ND 2016 INTERNATIONAL CONFERENCE ON SUSTAINABLE DEVELOPMENT (ICSD 2016), 2017, 94 : 453 - 455