Modeling Marshall stability of steel fiber reinforced asphalt concrete by genetic expression programming

Abstract

This study presents the potential of Genetic Expression Programming (GEP) computing paradigm to forecast the Marshall Stability of steel fiber reinforced asphalt concrete and has various mix proportions has been developed. Experimental details were used to construct the model. The steel fiber content (0%, 0.25%, 0.50%, 0.75%, 1.0%, 1.5%, 2.0% and 2.5%), percentage of bitumen (5%, 5.5% and 6.0%) and unit weights (2,465-2,515 (gr/cm3)) was used as input variables and Marshall Stability (kg) values were used as output variables. The performance of models was comprehensively judged using several statistical verification tools. Results have shown that developed GEP model has a strong potential for predicting the Marshall Stability of asphalt concrete without performing any experimental studies.