Determining the Drift in Reinforced Concrete Building Using ANFIS Soft Computing Modeling

Abstract

Earthquakes are considered as one of the most significant natural disasters that can potentially cause significant damages to structures. Displacement of buildings' floors is one of the serious failures in structures caused by earthquakes. In this paper, the drift of a concrete frame with the shear wall is estimated using ANFIS modeling. A dataset of 300 measured data points was used herein as the inputs for the ANFIS model. The dataset has totally six input parameters including frequency, magnitude, peak ground acceleration (PGA), and shear wave velocity (Vs) of an earthquake and the distance from the earthquake epicenter to use in the ANFIS model, while the model has just one output. Moreover, a sensitivity analysis was performed on the dataset in order to determine the efficiency of the individual input variables on the accuracy of the results. The results demonstrate that the ANFIS model is an effective model for predicting the drift in reinforced concrete structures. Finally, according to sensitivity analysis, the acceleration and shear wave velocity of an earthquake have the highest and lowers impacts on the accuracy of the results, respectively.