LP Methods for Fuzzy Regression and a New Approach

Cetintav B., ÖZDEMİR A. F.

6th International Conference on Soft Methods in Probability and Statistics, Konstanz, Almanya, 4 - 06 Ekim 2012, cilt.190, ss.183-191 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 190
  • Doi Numarası: 10.1007/978-3-642-33042-1_20
  • Basıldığı Şehir: Konstanz
  • Basıldığı Ülke: Almanya
  • Sayfa Sayıları: ss.183-191
  • Anahtar Kelimeler: Fuzzy linear regression, linear programming methods, LINEAR-REGRESSION, OUTLIERS
  • 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.