Prediction of splitting tensile strength from the compressive strength of concrete using GEP

Splitting tensile strength is one of the important mechanical properties of concrete that is used in structural design. In this paper, it is aimed to propose formulation for predicting cylinder splitting tensile strength of concrete by using gene expression programming (GEP). The database used for training, testing, and validation sets of the GEP models is obtained from the literature. The GEP formulations are developed for prediction of splitting tensile strength of concrete as a function of water-binder ratio, age of specimen, and 100-mm cube compressive strength. The training and testing sets of the GEP models are randomly selected from the complete experimental data. The GEP formulations are also validated with additional experimental data except from the data used in training and testing sets of the GEP models. GEP formulations’ results are compared with experimental results. Results of this study revealed that GEP formulations exhibited better performance to predict the splitting tensile strength of concrete.