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Earthquakes and Structures
  Volume 4, Number 5, May 2013 , pages 509-525
DOI: https://doi.org/10.12989/eas.2013.4.5.509
 


Neural network-based generation of artificial spatially variable earthquakes ground motions
Hossein Ghaffarzadeh, Mohammad Mahdi Izadi and Nima Talebian

 
Abstract
    In this paper, learning capabilities of two types of Arterial Neural Networks, namely hierarchical neural networks and Generalized Regression Neural Network were used in a two-stage approach to develop a method for generating spatial varying accelerograms from acceleration response spectra and a distance parameter in which generated accelerogram is desired. Data collected from closely spaced arrays of seismographs in SMART-1 array were used to train neural networks. The generated accelerograms from the proposed method can be used for multiple support excitations analysis of structures that their supports undergo different motions during an earthquake.
 
Key Words
    generation of artificial earthquake; neural networks; spatially varying earthquakes; response spectrum; SMART-1 array
 
Address
Hossein Ghaffarzadeh, Mohammad Mahdi Izadi and Nima Talebian: Department of Structural Engineering, University of Tabriz, Tabriz, Iran
 

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