• DocumentCode
    536195
  • Title

    Study on support vector machine in evalluation of bridge structural health monitoring

  • Author

    Wang, Jingyan ; Tan, Li ; Yu, Chongchong

  • Author_Institution
    Dept of Comput. & Inf. Eng., Beijing Technol. & Bus. Univ., Beijing, China
  • Volume
    2
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    430
  • Lastpage
    434
  • Abstract
    Structural distortion of bridge contains rich connotation information of bridge structures and possesses the features of nonlinear, sequential and small sample capacity. In this article, the evaluation model of bridge structural distortion is established by application of support vector machine and the practical monitoring data of Hangzhou Bay Bridge are taken as the study object. The feasibility and effectiveness of evaluation over bridge structural health state have been proved through test, and the superiority of least square support vector machine in distortion prediction has been shown on comparison of test results.
  • Keywords
    bridges (structures); condition monitoring; least squares approximations; structural engineering; support vector machines; Hangzhou bay bridge; bridge structural health monitoring; connotation information; distortion prediction; least square support vector machine; sample capacity; structural distortion; Kernel; Monitoring; Support vector machines; Tin; bridge structural health monitoring; distortion; least squares support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-6582-8
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2010.5658334
  • Filename
    5658334