TIME HISTORY ANALYSIS OF STRUCTURES FOR EARTHQUAKE LOADING BY WAVELET NETWORKS

Fast Wavelet Transforms (FWT) and Discrete Wavelet Neural Networks (DWN) are used for dynamic analysis of structures. A filter bank is used for the FWT and the number of points of the earthquake record is reduced. The DWN is used for approximating the dynamic responses of the structures. By such approximation, the dynamic analysis of the structure is not necessary if the structural properties are changed. Both feedforward neural networks and wavelet decompositions inspire this network. An algorithm of backpropagation type is proposed for training the network. In this network, the input is the damping ratio and the angular natural frequency of the structure and the output is the responses of the structures against these reduced points. After training the network, using the inverse wavelet transform, the results of the dynamic analysis are obtained for the original earthquake record from the output of the network. Some numerical examples are solved by the proposed method and the results are compared with those of the original record.