NEW METHOD OF GENERATING SPECTRUM COMPATIBLE ACCELEROGRAMS USING NEURAL NETWORKS

A new method is proposed for generating artificial earthquake accelero grams from response spectra. This method uses the learning capabilitie s of neural networks to developed the knowledge of the inverse mapping from the response spectra to earthquake accelerogram. In the proposed method the neural networks learn the inverse mapping directly from th e actual recorded earthquake accelerograms and their response spectra. A two-stage approach is used. In the first stage, a replicator neural network is used as a data compression tool. The replicator neural net work compresses the vector of the discrete Fourier spectra of the acce lerograms to vectors of much smaller dimension. In the second stage, a multi-layer feed-forward neural network learns to relate the response spectrum to the compressed Fourier spectrum. A simple example is pres ented, in which only 30 accelerograms are used to train the two-stage neural networks. This example demonstrates how the method works and sh ows its potential. (C) 1998 John Wiley & Sons, Ltd.