through the last three decades different seismological and engineering approaches for the generation of artificial earthquakes have been proposed. selection of an appropriate method for the generation of applicable artificial earthquake accelerograms (aeas) has been a challenging subject in the time history analysis of the structures in the case of the absence of sufficient recorded accelerogra...

In this paper, the probable range of the horizontal component of peak ground acceleration (PGA) is predicted as a function of focal depth, earthquake magnitude and epicentral distance, using artificial neural network (ANN). Three different ANN architectures (namely Feed Forward, Back Propagation and Radial Bias Networks) are used to develop the model. The three models are then compared, to deci...

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...

The main objective of this paper is to use ant optimized neural networks to generate artificial earthquake records. In this regard, training accelerograms selected according to the site geology of recorder station and Wavelet Packet Transform (WPT) used to decompose these records. Then Artificial Neural Networks (ANN) optimized with Ant Colony Optimization and resilient Backpropagation algorith...

this research intends to develop a method based on the artificial neural network (ann) to predict permanent earthquake-induced deformation of the earth dams and embankments. for this purpose, data sets of observations from 152 published case histories on the performance of the earth dams and embankments, during the past earthquakes, was used. in order to predict earthquake-induced deformation o...

stability and safety analysis of dams is a subject which has been studied in recent years by several researchers. researchers have used various methods and models for studying the stability of the dam. several methods are proposed for the analysis of earth dams under earthquakes. some of these methods are viscoelastic methods and semi static methods. each of these methods can be used as an appr...

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...

On 3 April 2017, a Mw 6.5 earthquake occurred in Botswana, representing the secondstrongest earthquake registered since 1949. Such an intraplate event occurred in a low seismic hazard area and was suspected to be an artificial earthquake induced by nearby anthropogenic activities (gas extraction). The possible relation between anthropogenic activities and the earthquake occurrence has been qual...

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...