Empirical predictive model for the (v max)/(a max) ratio of strong ground motions using genetic programming

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@Article{Jafarian20101523,
  author =       "Yaser Jafarian and Elnaz Kermani and 
                 Mohammad H. Baziar",
  title =        "Empirical predictive model for the (v max)/(a max)
                 ratio of strong ground motions using genetic
                 programming",
  journal =      "Computer \& Geosciences",
  volume =       "36",
  number =       "12",
  pages =        "1523--1531",
  year =         "2010",
  month =        dec,
  ISSN =         "0098-3004",
  DOI =          "doi:10.1016/j.cageo.2010.07.002",
  URL =          "http://www.sciencedirect.com/science/article/B6V7D-517YN79-1/2/f812ef6b3ddb0cdd20c12efbec9c4b09",
  keywords =     "genetic algorithms, genetic programming, Earthquake,
                 Predictive model, vmax/amax ratio, Frequency content",
  abstract =     "Earthquake-induced deformation of structures is
                 strongly influenced by the frequency content of input
                 motion. Nevertheless, state-of-the-practice studies
                 commonly use the intensity measures such as peak ground
                 acceleration (PGA), which are not frequency dependent.
                 The vmax/amax ratio of strong ground motions can be
                 used in seismic hazard studies as a parameter that
                 captures the influence of frequency content. In the
                 present study, genetic programming (GP) is employed to
                 develop a new empirical predictive equation for the
                 vmax/amax ratio of the shallow crustal strong ground
                 motions recorded at free field sites. The proposed
                 model is a function of earthquake magnitude, closest
                 distance from source to site (Rclstd), faulting
                 mechanism, and average shear wave velocity over the top
                 30 m of site (Vs30). A wide-ranging database of strong
                 ground motion released by Pacific Earthquake
                 Engineering Research Center (PEER) was used. It is
                 demonstrated that residuals of the final equation show
                 insignificant bias against the variations of the
                 predictive parameters. The results indicate that
                 vmax/amax increases through increasing earthquake
                 magnitude and source-to-site distance while magnitude
                 dependency is considerably more than distance
                 dependency. In addition, the proposed model predicts
                 higher (v max)/(a max) ratio at softer sites that
                 possess higher fundamental periods. Consequently, as an
                 instance for the application of the proposed model, its
                 reasonable performance in liquefaction potential
                 assessment of sands and silty sands is presented.",
  notes =        "See also \cite{Kermani:2009:IJCE}",
}

Genetic Programming entries for Yaser Jafarian Elnaz Kermani Mohammad Hassan Baziar

Citations