In this paper, the use of wavelet analysis and artificial neural networks for generating artificial earthquake accelerograms from target spectrum is suggested as a new method. This procedure uses the learning capabilities of neural network to expand the knowledge of the inverse mapping from response spectrum to earthquake accelerogram. In the first step, wavelet analysis is used to decompose ea...

the artificial accelerograms have been developed for assessing the dynamic response ofstructures. considering seismological properties of the site are necessary for the best simulation ofaccelerograms. the real recorded accelergrams for simulating earthquake phenomenon are used in thearma model. this is due to the fact that the arma model can be considered more advantageous than theothers.in th...

For seismic resistant design of critical structures, a dynamic analysis, based on either response spectrum or time history is frequently required. Due to the lack of recorded data and randomness of earthquake ground motion that might be experienced by the structure under probable future earthquakes, it is usually difficult to obtain recorded data which fit the necessary parameters (e.g. soil ty...

future design procedures for civil structures, especially those to be protected from extreme and blast relatedloads, will need to account for temporal evolution of their frequency content. there are, however, several instanceswhere acceleration time histories are required as seismic input. for example, to determine the ultimate resistance andto identify modes of structures’ failure, a nonlinear...

This paper deals with the well-known problem of generating spectrum-compatible synthetic accelerograms for the linear and non-linear time-history analyses of structural systems. A wavelet-based procedure has been used to decompose a recorded accelerogram into a desired number of time-histories with non-overlapping frequency contents, and then each of the time-histories has been suitably scaled ...

A new methodology is proposed to simulate accelerogram which is compatible to both linear and nonlinear design spectra. For this purpose, a wavelet-based parametric characterization of earthquake accelerogram is adopted and the parameters are optimized to tune its non-stationary features. A modified form of L-P basis is considered for wavelet transform which has the unique feature to decompose ...

The Hartley transform, a real-valued alternative to the complex Fourier transform, is presented as an efficient tool for the analysis and simulation of earthquake accelerograms. This paper is introduced a novel method based on discrete Hartley transform (DHT) and radial basis function (RBF) neural network for generation of artificial earthquake accelerograms from specific target spectrums. Acce...

A recently developed nonstationary stochastic model of strong earthquake ground motion is described. The model employs filtering of a white-noise process, where nonstationarity is achieved by modulating the intensity and varying the filter parameters in time. The model is fitted to a target accelerogram by matching a set of statistical measures that characterize the evolution of the intensity, ...

The paper is devoted on the problem of strong motion waves classification and real-time prognoses with neural network. As input information for the neural network are given the parameters of recorded part of accelerogram, principle axis transform and spectral characteristics of the wave. With the help of stochastic long-range dependence time series analyses are determined the separated phases o...