• DocumentCode
    2672185
  • Title

    GA based LS-SVM classifier for waste water treatment process

  • Author

    Hong, Yang ; Fei, Lou ; Yuge, Xu ; Jin, Liang

  • Author_Institution
    Sch. of Autom. Sci. & Eng., South China Univ. of Technol., Guangzhou
  • fYear
    2008
  • fDate
    16-18 July 2008
  • Firstpage
    436
  • Lastpage
    439
  • Abstract
    Least squares support vector machine (LS-SVM) combined with genetic algorithm (GA) are presented in this paper and this new algorithm can be a classifier in wastewater treatment process. The LS-SVM can overcome some shortcoming in the multilayer perception; meantime the GA can be used to tune the parameters of LS-SVM automatically and can escape from the blindness of man-made choice of the parameters of LS-SVM. The numerical experiments for classifying the operational state of the wastewater treatment process show that the proposed algorithm is effective and has less prediction error.
  • Keywords
    genetic algorithms; least squares approximations; pattern classification; support vector machines; wastewater treatment; control problem; genetic algorithm; least square support vector machine classifier; multilayer perception; wastewater treatment process; Automatic control; Automation; Genetic algorithms; Least squares methods; Neural networks; Pollution; Process control; Support vector machine classification; Support vector machines; Wastewater treatment; Classification accuracy; GA; LS-SVM; Wastewater treatment process;
  • 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.2008.4605860
  • Filename
    4605860