| Yazarlar |
Türkan Erbay Dalkılıç
Karadeniz Teknik Üniversitesi, Türkiye |
Prof. Dr. Kamile ŞANLI KULA
Ahi Evran Üniversitesi, Türkiye |
| Özet |
| While parameter estimation is done by the classical methods, there are a number of assumptions need to be satisfied, in the linear regression analysis. Key assumptions of linear regression are; no auto correlation, no or little multicollinearity, homoscedasticity and the errors have normal distribution. In this work, the case that independent variable has Pareto distribution to be discussed and an algorithm using adaptive networks suggested to parameter estimation where the k which is one of the parameters of the fuzzy membership functions is fuzzy. Also the parameter of fuzzy membership function is fuzzy the estimation process is based on type-II fuzzy logic. |
| Anahtar Kelimeler |
| Membership function | Pareto distribution | Type-II fuzzy logic |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | ESCI dergilerinde yayımlanan tam makale |
| Dergi Adı | GAZI UNIVERSITY JOURNAL OF SCIENCE |
| Dergi ISSN | 2147-1762 |
| Dergi Tarandığı Indeksler | ESCI: Emerging Sources Citation Index |
| Makale Dili | İngilizce |
| Basım Tarihi | 01-2017 |
| Cilt No | 30 |
| Sayı | 1 |
| Sayfalar | 251 / 258 |
