PROCEEDINGS IPMU '08
Linear Fuzzy Regression Using Trapezoidal Fuzzy Intervals
A. Bisserier, R. Boukezzoula and S. Galichet.
In this paper, a revisited approach for
possibilistic fuzzy regression methods is
proposed. Indeed, a new modified fuzzy
linear model form is introduced where
the identified model output can envelope
all the observed data and ensure a
total inclusion property. Moreover, this
model output can have any kind of
spread tendency. In this framework, the
identification problem is reformulated
according to a new criterion that assesses
the model fuzziness independently of
the collected data. The proposed concepts
are used in a global identification
process in charge of building a piecewise
model able to represent every kind
of output evolution.
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