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Parameter estimation by type-2 fuzzy logic in case that data set has outlier   
Yazarlar
Türkan Erbay Dalkılıç
Karadeniz Teknik Üniversitesi, Türkiye
Prof. Dr. Kamile ŞANLI KULA Prof. Dr. Kamile ŞANLI KULA
Kırşehir Ahi Evran Üniversitesi, Türkiye
Seda Sağırkaya Tolan
Özet
One of the problems encountered in estimating the unknown pa- rameters of the regression models is the presence of outliers in the data set. This situation may cause problems in providing some assumptions such as the normal distribution for the parameter estimation process and the homogeneity of the variances. The case of the presence of outlier observations in the data set, estimation methods based on fuzzy logic that can be minimized the level of impact of this data are emerged as available methods. If fuzzy logic is used in regression analysis, there are two main steps for parameter estimation. The first of these is to define the clusters that compose the data set, and the other is calculate the degree of membership to determining the contributions of the data to each model for the clusters. In this study, type-2 fuzzy clustering algo- rithm defined as an expansion of fuzzy c-means algorithm in the determination of membership degrees of data sets was benefited. The presence of outliers in the data set is addressed. An algorithm has been proposed to estimate the un- known belonging to parameters of the regression model using the membership degrees obtained relating to the cluster elements. The parameters were esti- mated using regression methods to examine the effectiveness of the algorithm that called robust methods, and the results obtained were compared.
Anahtar Kelimeler
Makale Türü Özgün Makale
Makale Alt Türü ESCI dergilerinde yayımlanan tam makale
Dergi Adı Communications Faculty Of Science University of Ankara Series A1Mathematics and Statistics
Dergi ISSN 1303-5991
Dergi Tarandığı Indeksler ESCI
Makale Dili İngilizce
Basım Tarihi 12-2020
Cilt No 69
Sayı 2
Sayfalar 199 / 210
Doi Numarası 10.31801/cfsuasmas.713755
Makale Linki http://dx.doi.org/10.31801/cfsuasmas.713755
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Parameter estimation by type-2 fuzzy logic in case that data set has outlier

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