Evaluation of Factors Affecting Compressive Strength of Concrete using Machine Learning

Abstract

Compressive strength of the concrete is important for analyzing the characteristics of the concrete. The compressive strength is necessary to know if the given mixture of concrete meets the specified requirements. For the sustainability of construction, the compressive strength must meet the required standards. Machine learning models have been really a handy tool for the analysis of a wide range of problems. Machine learning models can find the pattern or trends in the given data. The purpose of the paper is two folds. First, the evaluation of performance of different machine learning models (regression models) is done. In the second fold, the factors affecting compressive strength of the concrete are discussed. Different factors have different degrees of importance for various regressors. The importance of the factors is studied for different regressors and the conclusion is drawn regarding the importance of factors taken in the study.