Prediction of Concrete Compressive Strength using Machine Learning

Abstract

Concrete Compressive strength is the attribute that is used to measure the consistency of the concrete. The concrete's compressive strength is measured subject to the size and the quality of cement, slag, fly ash, etc. Measuring the compressive strength in real-time scenarios takes a lot of effort. Linear regression is a kind of Machine learning methods methods used to predict the compressive strength of the concrete based on the attributes of supervised learning methods. Linear regression of machine learning can be appropriate for predicting the compressive strength of the concrete. The Linear regression based model has been created and trained using the dataset from UCI Machine Learning Repository. The model's performance was also tested by using the metrics RMSE, and MSE. The model can predict the concrete compressive strength for any unknown value of the given attributes.