%0 Journal Article
%T A robust least squares fuzzy regression model based on kernel function
%J Iranian Journal of Fuzzy Systems
%I University of Sistan and Baluchestan
%Z 1735-0654
%A Khammar, A. H.
%A Arefi, M.
%A Akbari, M. G.
%D 2020
%\ 08/01/2020
%V 17
%N 4
%P 105-119
%! A robust least squares fuzzy regression model based on kernel function
%K distance
%K Kernel function
%K Least squares method
%K Outliers
%K Robust fuzzy regression
%R 10.22111/ijfs.2020.5409
%X In this paper, a new approach is presented to fit arobust fuzzy regression model based on some fuzzy quantities. Inthis approach, we first introduce a new distance between two fuzzynumbers using the kernel function, and then, based on the leastsquares method, the parameters of fuzzy regression model isestimated. The proposed approach has a suitable performance topresent the robust fuzzy model in the presence of different typesof outliers. Using some simulated data sets and some real datasets, the application of the proposed approach in modeling somecharacteristics with outliers, is studied.
%U https://ijfs.usb.ac.ir/article_5409_9f42718415f1e2c77d90e77b0b65b9f7.pdf