Seismic Behavior Prediction of Shear Structures Using by Artificial Neural Networks

Dynamic analysis of various structures against dynamic loading such as earthquake, wind, etc., has the time consuming process. Utilizing artificial neural networks (ANNs) simplify data processing operation in a board range area in engineering. In this paper at first efficient neural networks such as Back Propagation (BP), Radial Basis Function (RBF) and Generalized Regression (GR) are trained for predicting the displacements of Single Degree of Freedom (SDOF) system under dynamic loading and after that these methods are generalized for Multi Degree of Freedom (MDOF) system under earthquake loading. The performance of these networks are assessed and compared for predicting the exact displacements of SDOF and MDOF systems.

Seismic Behavior Prediction of Shear Structures Using by Artificial Neural Networks Keywords:

Dynamic analysis , Artificial neural networks , Radial basis function , Generalized regression , Back propagation , SDOF and MDOF systems