Moment capacity estimation of spirally reinforced concrete columns using ANFIS

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This paper presents a predictive model based on adaptive neuro-fuzzy inference system namely ANFIS to determine the moment capacity of spiral-reinforced concrete columns. For this purpose, five input parameters including the longitudinal reinforcement index, transverse reinforcement index, axial force, diameter to length ratio and also shear force were considered to estimate the moment capacity. A collection of experimental database applied to train and test the proposed system. This database includes 82 spiral-reinforced concrete columns (with flexure failure) which were reported in the literature and modified by PEER as a uniform database of cantilever columns. The model is created by Fuzzy C-means algorithm with four cluster and Gaussian membership functions, also trained and tested by 70 and 12 datasets, respectively. It was concluded that the model of this study with high accuracy could be able to estimate the moment capacity.

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