• DocumentCode
    2244719
  • Title

    Outlier identify based on BP neural network in dam safety monitoring

  • Author

    Li, Ning ; Li, Peng ; Xinling Shi ; Yan, Kai ; Ren, Wenping

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Yunnan Univ., Kunming, China
  • Volume
    2
  • fYear
    2010
  • fDate
    6-7 March 2010
  • Firstpage
    210
  • Lastpage
    214
  • Abstract
    In popular outlier processing methods, some emphasize on spotted outliers processing and some emphasize on isolated outliers processing. They have seldom processed outliers from the perspective of outlier producing mechanism. This paper aims at the problem of outliers in dam safety monitoring and an outlier identify method which based on BP neural network is presented. This method based on the mechanism of the dam monitoring data formation firstly created the BP neural network predicting model of monitoring data, then identify the outliers. The simulation results indicated that this method works with spotted outliers and isolated outliers and this method has a unique advantage on analysis of the outlier causes.
  • Keywords
    backpropagation; condition monitoring; dams; geotechnical engineering; neural nets; structural engineering computing; BP neural network predicting model; dam safety monitoring; outlier identify method; outlier processing methods; Additive noise; Labeling; MIMO; Monitoring; Neural networks; Rayleigh channels; Receiving antennas; Safety; Transmitters; Transmitting antennas; BP neural network; dam safety monitoring; outlier identifying; prediction model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
  • Conference_Location
    Wuhan
  • ISSN
    1948-3414
  • Print_ISBN
    978-1-4244-5192-0
  • Electronic_ISBN
    1948-3414
  • Type

    conf

  • DOI
    10.1109/CAR.2010.5456564
  • Filename
    5456564