evaluation of strength & components of concrete by using different machine learning methods

Concrete is an artificial stone that is made from a combination of cement, aggregate, water and additives. today, this natural stone has been used a lot in civil projects. one of the important characteristics of concrete is having a suitable efficiency for its use in different purposes and structures. the strength of concrete is highly dependent on its components and the amount and percentage of their composition. cement, water, granulation, lubricants, etc. are among the determining parameters that the smallest change in their amount changes the strength of concrete. predicting the strength of concrete is very difficult, but today, using machine learning techniques and having datasets, it is possible to predict the strength of concrete with a good approximation. in this paper, a data set of various concrete tests was analyzed using machine learning techniques and the results were compared. in this review, the linear regression and support vector regression with linear kernel algorithms are shown better results and less error than other algorithms.