Title of article :
A Comparison of Several Nonparametric Fuzzy Regressions with Trapezoidal Data
Author/Authors :
Razzaghnia, T. Department of Statistics - Islamic Azad University North Tehran Branch, Tehran , Danesh, S. Young Researchers and Elite Club - Islamic Azad university East Tehran Branch, Tehran , Maleki, A. Department of Statistics - Islamic Azad University West tehran Branch, Tehran
Abstract :
In this paper, three methods of nonparametric fuzzy regression with crisp input and
asymmetric trapezoidal fuzzy output, are compared. It analyzes the three nonparametric techniques in
statistics, namely local linear smoothing (L-L-S), K- nearest neighbor Smoothing (K-NN) and kernel
smoothing (K-S) with trapezoidal fuzzy data to obtain the best smoothing parameters. In addition, it
makes an analysis on three real-world datasets and calculates the goodness of fit to illustrate the
application of the proposed method.
Keywords :
Nonparametric Fuzzy Regression , Trapezoidal Fuzzy Numbers , Local Linear Smoothing (LL- S) , K-Nearest Neighbor Smoothing (K-NN) , Kernel Smoothing (K-S)
Journal title :
Journal of Applied Dynamic Systems and Control
