ROBUST FUZZY LINEAR REGRESSION BASED ON M-ESTIMATORS

  • SOHN BANG-YONG (Department of Computer Engineering, Daejin University)
  • Published : 2005.03.01

Abstract

The results of fuzzy linear regression are very sensitive to irregular data. When this points exist in a set of data, a fuzzy linear regression model can be incorrectly interpreted. The purpose of this paper is to detect irregular data and to propose robust fuzzy linear regression based on M-estimators with triangular fuzzy regression coefficients for crisp input-output data. Numerical example shows that irregular data can be detected by using the residuals based on M-estimators, and the proposed robust fuzzy linear regression is very resistant to this points.

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