SUPPORT VECTOR MACHINE (SVM) FOR MODELLING THE STRENGTH OF LIGHTWEIGHT FOAMED CONCRETE

Abstract

In construction industry, strength is a primary criterion in selecting a concrete for a particular application. Concrete used for construction gains strength over a long period of time after pouring. The characteristic strength of concrete that considered in structural design is defined as the compressive strength of a sample that has been aged for 28 days. So rapid and reliable prediction for the strength of concrete would be of great significance. Prediction of concrete strength, therefore, has been an active area of research and a considerable number of studies have been carried out. In this study, support vector machine model was proposed and developed for the prediction of concrete compressive strength at early age. The variables used in the prediction models were from the knowledge of the mix proportion elements and 7-day compressive strength. The models provide good estimation of compressive strength and yielded good correlations with the data used in this study relative to nonlinear multivariable regression. Moreover, the SVM model proved to be significant tool in prediction compressive strength of lightweight foamed concretes with minimal mean square errors and standard deviation.

Keywords

Foamed Concrete, SVM