Inverse modeling to derive wind parameters from wave measurements

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Charhate2008120,
  author =       "S. B. Charhate and M. C. Deo and S. N. Londhe",
  title =        "Inverse modeling to derive wind parameters from wave
                 measurements",
  journal =      "Applied Ocean Research",
  volume =       "30",
  number =       "2",
  pages =        "120--129",
  year =         "2008",
  ISSN =         "0141-1187",
  DOI =          "doi:10.1016/j.apor.2008.08.002",
  URL =          "http://www.sciencedirect.com/science/article/B6V1V-4TCGM50-1/2/69dcf477c9fc85235d0cc5df25e6a54a",
  keywords =     "genetic algorithms, genetic programming, Wave buoy,
                 Wave data, Wind data, Neural networks",
  abstract =     "The problem of deriving wind parameters from measured
                 waves is discussed in this paper. Such a need
                 reportedly arises in the field when the wind sensor
                 attached to a wave rider buoy at high elevation from
                 the sea level gets disconnected during rough weather,
                 or otherwise needs repairs. This task is viewed as an
                 inverse modeling approach as against the direct and
                 common one of evaluating the wind-wave relationship.
                 Two purely nonlinear approaches of soft computing,
                 namely genetic programming (GP) and artificial neural
                 network (ANN) have been used. The study is oriented
                 towards measurements made at five different offshore
                 locations in the Arabian Sea and around the western
                 Indian coastline. It is found that although the results
                 of both soft approaches rival each other, GP has a
                 tendency to produce more accurate results than the
                 adopted ANN. It was also noticed that the
                 equation-based GP model could be equally useful as the
                 one based on computer programs, and hence for the sake
                 of simplicity in implementation, the former can be
                 adopted. In case the entire wave rider buoy does not
                 function for some period, a common regional GP model
                 prescribed in this work can still produce the desired
                 wind parameters with the help of wave observations
                 available from anywhere in the region. A graphical user
                 interface is developed that puts the derived models to
                 their actual use in the field.",
}

Genetic Programming entries for S B Charhate M C Deo S N Londhe

Citations