2013 - India - Roughness Modelling With Artificial Neural Networks

It is a well established fact that the roughness is manifested as an effect of different individual

pavement deterioration parameters. Several studies have been oriented in the direction of

establishing the models capable of predicting the roughness. However, it was felt essential to

develop a model explaining the dynamics of different pavement deterioration parameters on

the roughness. In view of very limited studies reported in this direction, the present study is

carried out, first by grouping available data into homogeneous clusters and then model them

using Feed Forward Back Propagation Artificial Neural Network algorithm. K- Means

partitional clustering algorithm has been adopted for clustering the data. A new mathematical

algorithm has been proposed and used for optimizing the number of clusters, which is further

verified with the available standard validity indices. The present modeling attempt has

indicated strong correlation between the road roughness and the deterioration parameters viz

cracking, raveling, potholes, patching and rutting. The models developed for all the clusters

have shown decent statistical acceptability.