A Piecewise Type-2 Fuzzy Regression Model

Abstract

The type-2 fuzzy logic system permits us to model uncertainties existing in membership functions. Accordingly, this study aims to propose a linear and a piecewise framework for an interval type-2 fuzzy regression model based on the existing possibilistic models. In this model, vagueness is minimized, under the circumstances where the hcut of observed value is included in predicted value. In this model both primary and secondary membership function of predicted value fit the observed value. Developing the proposed model to piecewise model makes it helpful in dealing with the fluctuating data. This model, without the additional complexities, demonstrates its ability compared to previous type-2 fuzzy models.

Keywords

• Interval type-2 fuzzy regression
• Quadratic programming
• type-2 fuzzy piecewise regression