Machine Learning Techniques for Analysing the Seismic Response in Multistorey Steel Structures

This paper provides a detailed analysis that uses an Artificial Neural Network (ANN) in forecasting the seismic response in multistorey steel structures.A comprehensive framework has been developed to conduct a parametric study, with the intention of leveraging the outcomes from dynamic analysis, as inputs in the ANN.The framework explores the process of selecting earthquakes by utilizing seismic response spectrums and a nonlinear finite element (FE) model that introduces varied geometric properties, member sizes, and peak ground accelerations to derive eigenfrequencies, horizontal drift and base shear.Results indicate a satisfactory accuracy of the trained Artificial Neural Networks to predict the dynamic response.