  In this article, a Hybrid Fuzzy Regression Model with Asymmetric Triangular
Fuzzy Coefficients and optimized $h-$value in Generalized Linear Models (GLM)
framework have been developed. The weighted functions of Fuzzy Numbers rather
than the Expected value of Fuzzy Number is used as a defuzzification procedure.
We perform the new model on a numerical data (Taylor and Ashe, 1983) to predict
incremental payments in loss reserving. We prove that the new Hybrid Model with
the optimized $h-$value produce better results than the classical GLM according
to the Reserve Prediction Error and Reserve Standard Deviation.
