Prediction of elastic modulus of normal and high strength concrete using ANFIS and optimal nonlinear regression models

Abstract This article proposes an adaptive network-based fuzzy inference system (ANFIS) model and three optimized nonlinear regression models to predict the elastic modulus of normal and high strength concrete. The optimal values of parameters for nonlinear regression models are determined with differential evolution (DE) algorithm. The elastic modulus predicted by ANFIS and nonlinear regression models are compared with the experimental data and those from other empirical models. Results demonstrate that the ANFIS model outperforms the nonlinear regression models and most of other predictive models proposed in the literature and therefore can be used as a reliable model for prediction of elastic modulus of normal and high strength concrete.

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