Speculation of compressive strength of concrete in real-time

Abstract

Prediction of compressive strength of concrete is a tedious and time consuming progress, so it has to be replaced by means of some modern techniques in order to overcome difficulties. With the growth of the construction industry, there is a need to give quality in it. Improper Testing of the construction materials may lead to the collapse of the entire building. In our Country, most of the construction work is done with concrete, So the first and foremost thing is to examine the compressive strength of the concrete which gives a better idea about durability, reliability, and grade of the concrete. Testing of concrete usually takes place on the 28-day of concrete placement. Human error occurs very commonly in casting the concrete by mixing improper proportions, poor compaction and adapting wrong methods for testing the specimen. If any of the above factors occur it is tedious to obtain the proper process since it has to be carried out from first. Therefore, it has to be taken into consideration that strength yielded to satisfy the strength to be carried. It gives out the speculation of target strength of the concrete using machine learning algorithms with improved accuracy and also a comparison of the result is made between Support Vector Machine (SVM) and Artificial Neural Network (ANN) by 78% and 96%. From the approaches it is found to be, the features can be universal and imparted to all other factors depending concrete strength. The practices of these procedures will lead considerably to concrete quality control.