Prediction of concrete properties based on rough sets and support vector machine method
Guohua Liu · Journal of Hydroelectric Engineering · 2011
This study develops a new prediction model of concrete properties that uses independent variables of all dosages of raw materials and their qualities and dependent variables of initial slump and cubic compressive strengths at the age of 7,28 days.In this model,a rough sets(RS) method is adopted for reduction of the independent variables,and a method of support vector machine regression(SVR) for prediction of concrete properties.Two groups of sample are collected and tested,one containing 169 sets of mixture with fly ash as admixture and the other containing 135 sets of mixture with fly ash and slag as admixture.Among these groups,one third of the mixtures are randomly selected for prediction verification.The test results show a better prediction accuracy of the new model than the linear regression method and more stable performances than the BP artificial network model.Through a sensitivity analysis it is revealed that the RS-SVM model is able to reflect the dependencies of concrete properties.