Abstract:

In order to reasonably determine the input parameters in pavement structure design, a self-organized feature mapping neural network is introduced and its weight is trained with Matlab. Then, by taking the convergence of the training as the classification rule, a seasonal roadway classification is made according to such important parameters as temperature, traffic and rainfall. Moreover, pavement structure analysis and material design are performed according to the classification results. The proposed classification method is proved effective in determining reasonable design parameters of pavement. Thus, it greatly prolongs the service life of pavement and improves the economic benefit of road investment.

Key words: seasonal roadway classification, neural network , self-organizing feature map, pavement structure design