Author/Authors :
YALAZ, Seçil Dicle Üniversitesi - Fen Fakültesi - Matematik Bölümü, Turkey , ATAY, Arife Dicle Üniversitesi - Fen Fakültesi - Matematik Bölümü, Turkey , TOPRAK, Z. Fuat Dicle Üniversitesi - Mühendislik Fakültesi - İnşaat Mühendisliği Bölümü, Turkey
Title Of Article :
Fuzzy linear regression for the data which is fuzzified with SMGRT method
Abstract :
In classical regression analysis a difference is occurred between the observed dependent variable and estimates of the generated models. This difference is generally caused by the assumption of that the observed dependent variable has to be normally distributed with a constant variance and zero (0) average. In fuzzy regression analysis this difference is considered to be the blurring of the model structure. for the data which is appropriate for the fuzzy regression analysis instead of classical regression analysis due to certain restrictions, if the data does not include fuzzy variables, using probabilistic models may become mandatory. However, because of certain restrictions there are cases using of probabilistic model is not appropriate. We generate a fuzzy linear regression equation with Fuzzy Least Square Regression (FLSR) model. Here nonfuzzy variables are fuzzified with a new method SMRGT to use models have fuzzy variables. In conclusion, classical linear regression and fuzzy linear regression were applied a data set, and these two approaches performances were compared by using different measures.
NaturalLanguageKeyword :
Fuzzy Regression , Probabilistic Model , FLSR Model , Diamond Model , SMRGT Method
JournalTitle :
Erciyes University Journal Of The Institute Of Science and Technology
