To acquire new knowledge through earthquake ground motion evaluation from a perspective, the authors attempted to create site-specific model by machine learning using records obtained in past as training data. The epicentral direction and response duration time of motion, which had not been addressed conventional attenuation relations, were also examined. Overall, observed values evaluated mode...

a fast and accurate synthetic aperture radar raw data generator of moving targets has high importance, especially in the applications of ground moving target indication. in this paper, in the hybrid time-frequency domain, a fast algorithm for strip mode sar raw data generation of moving targets has been proposed. using this simulator, in different conditions in terms of target motion speed, acc...

This paper presents an application of neural network approach for the prediction of peak ground acceleration (PGA) using the strong motion data from Turkey, as a soft computing technique to remove uncertainties in attenuation equations. A training algorithm based on the Fletcher–Reeves conjugate gradient back-propagation was developed and employed for three sample sets of strong ground motion. ...

I outline a referenced empirical approach to the development of groundmotion prediction equations (GMPEs). The technique is illustrated by using it to develop GMPEs for eastern North America (ENA). The approach combines the ENA ground-motion database with the empirical prediction equations of Boore and Atkinson (2008) for the reference region of western North America (WNA). The referenced empir...

There has been a significant increase in earthquakes in Central and Eastern US (CEUS) in recent years. This increase in seismicity has been associated with human activities like wastewater injection, and is referred to as induced seismicity. One of the components for hazard and risk calculation from induced seismicity is the level of ground shaking expected from an earthquake at a site of inter...