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New method for generation of artificial earthquake record by new model in compression and Artificial Neural Networks

In this paper, the use of wavelet analysis and artificial neural networks for generating artificial earthquake accelerograms from the target spectra is suggested as a new method. This procedure uses the learning capabilities of neural network to expand the knowledge of the inverse recording from response spectra to earthquake accelerogram. In the first step, wavelet analysis is used to decompose earthquake accelerograms to several levels in which each level covers a special range of frequencies, and then for every level a neural network is trained to learn to relate the response spectra to wavelet coefficients. Finally, the generated accelerogram using inverse discrete wavelet transform is obtained. An example is presented to demonstrate the effectiveness of the proposed method.