• Title of article

    LS-SVM Method for Fuzzy Nonlinear Regression

  • Author/Authors

    Teksen, Ümran M. Selcuk University - Faculty of Science - Department of Statistics, Turkiye , Genç, Asır Selcuk University - Faculty of Science - Department of Statistics, Turkiye

  • From page
    53
  • To page
    60
  • Abstract
    In this study LS-SVM method is applied for fuzzy nonlinear regression whose input and output are fuzzy numbers. The method solves any problem of classification or regression via transforming to a quadratic problem without running into local solutions. This method is favourable owing to independent from a model. In this study, two practises are applied to linear and nonlinear data.
  • Keywords
    Fuzzy Nonlineer Regression , Least Squares Support Vector Machine
  • Journal title
    Selcuk Journal of Applied Mathematics
  • Journal title
    Selcuk Journal of Applied Mathematics
  • Record number

    2551935

    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=10&DC=2551935