… is to revisit some theoretical works about fuzzy regression techniques [5] and to propose …
tical use in fuzzy model identification easier. According to [5], fuzzy regression techniques can …

… -points and regression parameters free of non-differentiability. We transform a piecewise
regression model into a fuzzy class model and then employ a fuzzy classification maximum …

… the piecewise concept to implement fuzzy piecewise regression. This work proposes a
general fuzzy piecewise regression analy… obtain the fuzzy regression model and changepoints. …

… The type-2 fuzzy logic system permits us to model uncertainties existing in membership …
propose a linear and a piecewise framework for an interval type-2 fuzzy regression model based …

… This article presents a new hybrid change detection method by integrating fuzzy logic with
piecewise linear regression (PLR) as applied to the Yukon River Basin (YRB) in Alaska, USA, …

… In this paper, fuzzy linear regression with fuzzy input–output data is introduced in … and fuzzy
output is introduced in greater detail. In Section 4, characteristics of the piecewise regression …

… In this paper, we demonstrated a two-stage fuzzy linear piecewise regression analysis
method which can predict PLT, annual shipments, and change points in the PLC. The new …

… for possibilistic fuzzy regression methods is proposed. Indeed, a new modified fuzzy linear
… In this section, the previous identification method is used to identify a piecewise fuzzy linear …

… piecewise concept to implement fuzzy piecewise regression for solving nonlinear turbulent
time-series trends. We apply a general fuzzy piecewise regression … the regression model and …

… This study proposes fuzzy multiple objective programming to determine the measure of
fitness and the number of change-points in an interval piecewise regression model. To increase …