Name
Abstract | ||
|---|---|---|
In this paper, a new general approach is presented to fit a fuzzy regression model when the response variable and the parameters of model are as fuzzy numbers. In this approach, for estimating the parameters of fuzzy regression model, a new definition of objective function is introduced based on the different loss functions and under the averages of differences between the alpha-cuts of errors. The application of the proposed approach is studied using a simulated data set and some real data sets in the presence of different types of outliers. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/s00500-020-05441-2 | SOFT COMPUTING |
Keywords | DocType | Volume |
Goodness of fit, Loss function, Outlier data, Robust fuzzy regression | Journal | 25 |
Issue | ISSN | Citations |
2 | 1432-7643 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amir Hamzeh Khammar | 1 | 0 | 0.34 |
| Mohsen Arefi | 2 | 24 | 3.82 |
| Mohammad Ghasem Akbari | 3 | 31 | 12.04 |