Contents V4, No.2, 2013

  • PARAMETER ESTIMATION BASED TYPE-II FUZZY LOGIC
    K.S. KULA , T.E. DALKILIC 2 (pp. 187-193)
  • Abstract.

    Regression analysis is an area of statistics that deals with the investigation of the dependence of a variable upon one or more variables. Recently, much research has studied fuzzy estimation. The fuzzy regression method can be used to obtain unknown parameters of regression models based fuzzy data. In this study, we will use the ANFIS for parameter estimation and propose an algorithm in case where the independent variables are fuzzy sets. These sets are type-II fuzzy sets because of characterized by a Gaussian membership function with fuzzy mean.

    Keywords:

    type-II fuzzy logic, membership function, regression analysis, parameter estimation

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