RT - Journal Article
T1 - GENERATION OF MULTIPLE SPECTRUM-COMPATIBLE ARTIFICIAL EARTHQUAKE ACCELEGRAMS WITH HARTLEY TRANSFORM AND RBF NEURAL NETWORK
JF - IUST
YR - 2014
JO - IUST
VO - 4
IS - 1
UR - http://ijoce.iust.ac.ir/article-1-162-en.html
SP - 59
EP - 75
K1 - Hartley transform
K1 - RBF neural network
K1 - artificial earthquake accelerograms
AB - 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. Acceleration time histories of horizontal earthquake ground motion are obtained by the capability of learning of RBF neural network to expand the knowledge of the inverse mapping from the response spectrum to earthquake accelerogram. In the first step, Hartley transform is used to decompose earthquake accelerograms, then a RBF neural network is trained to learn to relate the response spectrum to Hartley spectrum. Finally, the generated accelerogram using inverse discrete Hartley transform is obtained from target spectrum. Approximately 200 uniformly scaled horizontal ground motion records from recent Iranâ€™s earthquakes are used to decompose with real Hartley transform and train networks.
LA eng
UL http://ijoce.iust.ac.ir/article-1-162-en.html
M3
ER -