Open AccessModeling of Compressive Strength of Concrete using Gaussian Membership Function
Author(s) -
M.S. Deepak,
B Final
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.b1029.1292s219
Subject(s) - compressive strength , aggregate (composite) , mean squared error , fuzzy logic , fly ash , gaussian , mathematics , approximation error , correlation coefficient , materials science , computer science , statistics , composite material , physics , artificial intelligence , quantum mechanics
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.