Prediction of compressive and splitting tensile strength of concrete with fly ash by using gene expression programming

The mechanical properties of concrete are one of the most important properties in a design code. Accurate prediction models for mechanical properties are always desirable. Given environmental benefits, fly ash (FA) is often used as a replacement for Portland cement. In this study, two mechanical properties of concrete with FA, that is, compressive strength f 0 co THORN and splitting tensile strength f sto THORN were modeled by using gene expression programming (GEP). The GEP models were compared with response surface methodology, multiple linear and nonlinear regression. The sensitivity and parametric analysis were also performed. In addition, the influence of parameters of the GEP algorithm on the performance of the developed GEP models was evaluated by testing various linking functions, head sizes, number of genes, number of chromosomes, and fitness functions. It was revealed that the models developed by GEP have high predictive and generalization capability for both f 0 c and f st of concrete with FA as compared with the other modeling techniques.