Name
Abstract | ||
|---|---|---|
We propose a new method for computation of fuzzy regression that is simple and gives good solutions. We consider two cases: First, when only the dependent variable is fuzzy, our approach is given and is compared with those suggested in the literature. Secondly, when both dependent and independent variables are fuzzy, our approach is extended and compared with those given in the literature. In each case, a simple example is used to compare the competing approaches. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1016/j.ejor.2004.01.039 | European Journal of Operational Research |
Keywords | Field | DocType |
Fuzzy sets,Fuzzy regression,Linear programming | Defuzzification,Regression analysis,Fuzzy logic,Algorithm,Fuzzy set,Variables,Fuzzy associative matrix,Fuzzy number,Mathematics,Linear regression | Journal |
Volume | Issue | ISSN |
166 | 1 | 0377-2217 |
Citations | PageRank | References |
57 | 2.93 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mehran Hojati | 1 | 88 | 7.11 |
| C. R. Bector | 2 | 197 | 19.95 |
| Kamal Smimou | 3 | 62 | 3.68 |