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Fuzzy logic modeling of compressive strength of high-strength concrete (HSC) with supplementary cementitious material
This paper presents application of fuzzy logic technique (Gaussian and Triangular) for developing a model for predicting the compressive strength of high-strength concrete having supplementary cementitious materials. It also helps in optimizing the constituents available and reducing the cost and efforts in studying design to develop mixes by pre-defining suitable range for experimenting. Supplementing concrete with various industrial byproducts requires proper evaluation of concrete’s characteristics because of varying proportions and parallel use. Fuzzy modeling is especially useful in estimating the compressive strength in such cases, as it precisely takes into account the absence of well-defined criteria for preparing concrete. To judge the performance of the model, correlation coefficient, mean absolute error, and root mean square error have been adopted as the comparative measures against the experimental results obtained from the literature. The results are further affirmed by the model developed using artificial neural network technique.
Fuzzy logic modeling of compressive strength of high-strength concrete (HSC) with supplementary cementitious material
This paper presents application of fuzzy logic technique (Gaussian and Triangular) for developing a model for predicting the compressive strength of high-strength concrete having supplementary cementitious materials. It also helps in optimizing the constituents available and reducing the cost and efforts in studying design to develop mixes by pre-defining suitable range for experimenting. Supplementing concrete with various industrial byproducts requires proper evaluation of concrete’s characteristics because of varying proportions and parallel use. Fuzzy modeling is especially useful in estimating the compressive strength in such cases, as it precisely takes into account the absence of well-defined criteria for preparing concrete. To judge the performance of the model, correlation coefficient, mean absolute error, and root mean square error have been adopted as the comparative measures against the experimental results obtained from the literature. The results are further affirmed by the model developed using artificial neural network technique.
Fuzzy logic modeling of compressive strength of high-strength concrete (HSC) with supplementary cementitious material
Aggarwal, Paratibha (Autor:in) / Aggarwal, Yogesh (Autor:in) / Siddique, Rafat (Autor:in) / Gupta, Sakshi (Autor:in) / Garg, Harshit (Autor:in)
Journal of Sustainable Cement-Based Materials ; 2 ; 128-143
01.06.2013
16 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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