Abstract
Tensile related cracking for asphalt mixtures is one of the major distresses for asphaltic pavements. Many of the pavements distortions were a straight and non-straight wards results for heterogeneity of values of the stiffness in the local produced hot asphalt mixes. This research concentrates on constructing an artificial neural network (ANN) to define the influence of natures and dosages of the additives, temperature, and time of loading on the stiffness. This study provides an (ANN) model to estimate the stiffness of hot mix asphalt (HMA). The analysis was showed that a good relationship there is a good representation between the actual and predicted values with a coefficient of determination of 88.6%.
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