A robust least squares fuzzy regression model based on kernel function
Publish place: Iranian Journal of Fuzzy Systems، Vol: 17، Issue: 4
Publish Year: 1399
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJFS-17-4_009
تاریخ نمایه سازی: 30 خرداد 1400
Abstract:
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.
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Authors
A. H. Khammar
Department of Statistics, Faculty of Mathematical Sciences and Statistics, University of Birjand, Birjand, Iran
M. Arefi
Department of Statistics, Faculty of Mathematical Sciences and Statistics, University of Birjand, Birjand, Iran
M. G. Akbari
Department of Statistics, Faculty of Mathematical Sciences and Statistics, University of Birjand, Birjand, Iran