LP Methods for Fuzzy Regression and a New Approach

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Çetintav B., Özdemir A. F.

Synergies of Soft Computing and Statistics for Intelligent Data Analysis , cilt.190, ss.183-191, 2013 (Scopus)

• Yayın Türü: Makale / Tam Makale
• Cilt numarası: 190
• Basım Tarihi: 2013
• Dergi Adı: Synergies of Soft Computing and Statistics for Intelligent Data Analysis
• Derginin Tarandığı İndeksler: Scopus
• Sayfa Sayıları: ss.183-191
• Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Linear Programming (LP) methods are commonly used to construct

fuzzy linear regression (FLR) models. Probabilistic Fuzzy Linear Regression

(PFLR) [9] and Unrestricted Fuzzy Linear Regression (UFLR) [3]

are two of the mostly applied models that employ LP methods. In this study,

a modified fuzzy linear regression model which use LP methods is proposed.

PFLR, UFLR and proposed model compared in terms of mean squared error

(MSE) and total fuzziness by using two simulated and one real data set.