Determination of Optimum Bitumen Content and Marshall Stability Using Neural Networks for Asphaltic Concrete Mixtures

Neural Networks technology provides several reliant analysis in many science and technology applications. In particular neural network is often applied to the development of statistical models for intrinsically non-linear systems, since neural networks behave better in complex conditions. In this research, applications of neural networks in determination of optimum bitumen content, Marshall Stability and Marshall Quotient of asphaltic concrete mixtures were investigated. To determine the properties of asphaltic concrete mixtures using neural networks, samples were collected from different regions in Mecca area during construction and tested at laboratories of Umm Al-Qura University for bitumen content, gradation of aggregate, Marshall Stability, Marshall Quotient determination. The conventional models for asphaltic concrete mixtures were developed on the basis of data collected. Part of the data set was used for validation. Suitability of using neural networks in developing a neural network model of the OBC, Marshall Stability and Marshall Quotient for asphaltic concrete mixtures was found; the models were developed and validated.