Application of Machine Learning in the Prediction of Compressive Strength of Concrete

Abstract

In this paper, the data of compressive strength of concrete are modeled by decision tree, boosting, random forest, artificial neural network and support vector machine methods. Tenfold cross-validation is adopted to assess the performance of these methods in terms of the prediction accuracy. It is seen that the Random Forest method has the best performance in general.