نویسندگان | Mohsen Arefi,Mohammad Ghasem Akbari |
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نشریه | Iranian Journal of Fuzzy Systems |
شماره صفحات | 105-119 |
شماره سریال | 17 |
شماره مجلد | 4 |
ضریب تاثیر (IF) | 0.56 |
نوع مقاله | Full Paper |
تاریخ انتشار | 2020 |
رتبه نشریه | ISI |
نوع نشریه | الکترونیکی |
کشور محل چاپ | ایران |
نمایه نشریه | JCR،isc،Scopus |
چکیده مقاله
In this paper, a new approach is presented to fit a robust fuzzy regression model based on some fuzzy quantities. In this approach, we first introduce a new distance between two fuzzy numbers using the kernel function, and then, based on the least squares method, the parameters of fuzzy regression model is estimated. The proposed approach has a suitable performance to present the robust fuzzy model in the presence of different types of outliers. Using some simulated data sets and some real data sets, the application of the proposed approach in modeling some characteristics with outliers, is studied.
tags: Distance, kernel function, least squares method, outliers, robust fuzzy regression