Abstract
A method for predicting development of rut depth in asphalt pavements in Hokuriku region was developed by applying Neural Network System (NNS). A three layer NNS with input nodes for IC section, subugrade type, lane type, surface type and the number of large vehicles and an output node for rut depth was employed. The model was established by inputing performance data of asphalt pavements in Hokuriku region. The predicted relationship between rut depth and the number of large vehicles agrees well with observed ones. The effects of the input parameters on rut depth development were discussed based on the predicted curves.
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