Neural network based classification of road pavement structures

Roads have formed the basic infrastructure of commerce since flints and other tools and artifacts were first exchanged along the trade routes of prehistory. Roadways are very large, in volume, in extent, and in value. They also wear out, and their useful life is directly proportional to their initial strength and inversely proportional to the number of heavy goods vehicles using them. Therefore, the increasing complexity of road transportation needs advanced techniques for effective design of pavements. This paper proposes an intelligent technique using neural networks to classify different types of road pavement structures, which is essential in estimating bearing capacities and load equivalency factors of pavements under different loadings.