000010067 001__ 10067
000010067 005__ 20141205154141.0
000010067 04107 $$aeng
000010067 046__ $$k2008-10-12
000010067 100__ $$aGhaffarzadeh, Hosein
000010067 24500 $$aArtificial Generation of Spatially Varying of Seismic Ground Motion Using ANNs

000010067 24630 $$n14.$$pProceedings of the 14th World Conference on Earthquake Engineering
000010067 260__ $$b
000010067 506__ $$arestricted
000010067 520__ $$2eng$$aDuring an earthquake, the motion of the ground spatially changes, in both amplitude and phase. The spatial variation of seismic ground motions has an important effect on the response of large structures such as bridges and dams. To be able to simulate seismic ground motions which vary in space, a representing spatial variability model is required. Data collected from closely spaced arrays of seismographs such as SMART-1 array in Loting, Taiwan have enabled researchers to produce useful spatial variability models to model spatial excitation. In this paper a simulation technique for the generation of artificial spatially variable seismic ground motions was presented using Arterial Neural Networks (ANNs). A simplified neural network based procedure was used to generate artificial spatial varying accelerograms from the response spectrum of an earthquake.

000010067 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000010067 653__ $$aNeural Network, Artificial Spatial Varying Earthquake, Response Spectra

000010067 7112_ $$a14th World Conference on Earthquake Engineering$$cBejing (CN)$$d2008-10-12 / 2008-10-17$$gWCEE15
000010067 720__ $$aGhaffarzadeh, Hosein$$iIzadi, Mohammad Mehdi
000010067 8560_ $$ffischerc@itam.cas.cz
000010067 8564_ $$s304081$$uhttps://invenio.itam.cas.cz/record/10067/files/02-0174.pdf$$yOriginal version of the author's contribution as presented on CD, Paper ID: 02-0174.
000010067 962__ $$r9324
000010067 980__ $$aPAPER