ARTIFICIAL NEURAL NETWORK AND ENTROPY APPROACH IN FUZZY NONLINEAR REGRESSION
Küçük Resim Yok
Tarih
2012
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Selçuk Üniversitesi
Erişim Hakkı
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
Özet
Fuzzy nonlinear regression (FNR) is different from classic regression models just because its output consists of fuzzy numbers. Predictions are realized by FNR models for the cases in which both input variables are nonlinearly related and output variable is fuzzy. Besides, a FNR model may be used to construct a probability interval for the output variable precisely. It is important to note that an entropy-based approach to FNR models results in smaller propagations for fuzzy intervals.
Fuzzy nonlinear regression (FNR) is different from classic regression models just because its output consists of fuzzy numbers. Predictions are realized by FNR models for the cases in which both input variables are nonlinearly related and output variable is fuzzy. Besides, a FNR model may be used to construct a probability interval for the output variable precisely. It is important to note that an entropy-based approach to FNR models results in smaller propagations for fuzzy intervals.
Fuzzy nonlinear regression (FNR) is different from classic regression models just because its output consists of fuzzy numbers. Predictions are realized by FNR models for the cases in which both input variables are nonlinearly related and output variable is fuzzy. Besides, a FNR model may be used to construct a probability interval for the output variable precisely. It is important to note that an entropy-based approach to FNR models results in smaller propagations for fuzzy intervals.
Açıklama
Anahtar Kelimeler
Nonlinear regression, Nonlinear regression, neural networks, neural networks, fuzzy set theory, fuzzy set theory, entropy approach, entropy approach
Kaynak
Journal of Selcuk University Natural and Applied Science
WoS Q Değeri
Scopus Q Değeri
Cilt
1
Sayı
1
Künye
Kahraman, U. M., Evren, A. (2012). Artıfıcıal Neural Network and Entropy Approach ın Fuzzy Nonlınear Regressıon. Journal of Selcuk University Natural and Applied Science, 1, (1), 14-29.
