• DocumentCode
    2669112
  • Title

    Application of multiple SVM classifier fusion technique in freeway automatic incident detection

  • Author

    Zhili, Cai ; Guiyan, Jiang

  • Author_Institution
    Shandong Jiaotong Univ., Jinan
  • fYear
    2008
  • fDate
    16-18 July 2008
  • Firstpage
    581
  • Lastpage
    585
  • Abstract
    Based on stating the principle of support vector machine (SVM) classifier, this paper analyses the data collected traits by fixed detectors and the traffic characteristics of freeway chiefly. Also, this paper proposes traffic pattern eigenvectors by data of several continuous time intervals for the single traffic parameter, puts forward multiple SVM classifier fusion models and operation flow, as well as analyzing results after simulation.
  • Keywords
    pattern classification; sensor fusion; support vector machines; traffic engineering computing; freeway automatic incident detection; multiple SVM classifier fusion technique; support vector machine classifier; traffic pattern eigenvectors; Analytical models; Data analysis; Detectors; Educational institutions; Electronic mail; Pattern analysis; Support vector machine classification; Support vector machines; Traffic control; Transportation; AID; Data fusion; Freeway; SVM; SVM Classifier;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference, 2008. CCC 2008. 27th Chinese
  • Conference_Location
    Kunming
  • Print_ISBN
    978-7-900719-70-6
  • Electronic_ISBN
    978-7-900719-70-6
  • Type

    conf

  • DOI
    10.1109/CHICC.2008.4605683
  • Filename
    4605683