Parameter Estimation Based Type II Fuzzy Logic
Yazarlar (2)
Prof. Dr. Kamile ŞANLI KULA
Kırşehir Ahi Evran Üniversitesi, Türkiye
Türkan Erbay Dalkılıç
Karadeniz Teknik Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (Uluslararası alan indekslerindeki dergilerde yayınlanan tam makale) | ||
| Dergi Adı | TWMS JOURNAL OF PURE AND APPLIED MATHEMATICS | ||
| Dergi ISSN | 2076-2585 Wos Dergi | ||
| Dergi Tarandığı Indeksler | MathSciNet | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2013 |
| Cilt / Sayı / Sayfa | 4 / 2 / 187–193 | DOI | – |
| Makale Linki | http://www.twmsj.az/Indexing.aspx | ||
| Özet |
| Regression analysis is an area of statistics that deals with the investigation of the dependence of a variable upon one or more variables. Recently, much research has studied fuzzy estimation. The fuzzy regression method can be used to obtain unknown parameters of regression models based fuzzy data. In this study, we will use the ANFIS for parameter estimation and propose an algorithm in case where the independent variables are fuzzy sets. These sets are type-II fuzzy sets because of characterized by a Gaussian membership function with fuzzy mean. |
| Anahtar Kelimeler |
| type-II fuzzy logic | membership function | regression analysis | parameter estimation |
