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Abstract
This study investigates the feasibility of a neuro-fuzzy (NF) approach for the modelling of shear strength of reinforced concrete (RC) beams without web reinforcement. The proposed NF model is based on a wide range of experimental data (664 tests) gathered from the literature from 56 separate studies. Various types of membership functions (MFs) such as Gaussian, Gaussian combination, generalised bell-shaped, triangular-shaped and trapezoidal-shaped MFs are evaluated for varying number of MFs to obtain the optimum NF model. The accuracy of the proposed NF model is compared with accuracies of current design codes and existing shear strength equations and found to be more accurate.
Acknowledgements
This research was supported by the Gaziantep University Project Research Unit.