Modeling of Compressive Strength of Concrete using Gaussian Membership Function

Abstract

This paper presents an application of fuzzy logic to forecast the compressive strength of concrete. The fuzzy model examines 7 different input parameters that comprises: Cement, Coarse aggregate(CA), Super plasticizer(SP), Fine Aggregate(FA), Slag, Fly ash, Water(W), and 28 days compressive strength is taken as the output parameter. By using Gaussian membership function, the fuzzy logic technique is used for developing models. For assessing the results of FL model with experimental results, root mean square error, mean absolute error and correlation coefficient are used. The results showed that FL can be a better modeling tool and an another technique for predicting the concrete’s compressive strength.