Genetic Programming to Estimate Coastal Waves from Deep Water Measurements

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Ruchi:2008:IJED,
  author =       "Ruchi Kalra and M. C. Deo and Raj Kumar and 
                 Vijay K. Agarwal",
  title =        "Genetic Programming to Estimate Coastal Waves from
                 Deep Water Measurements",
  journal =      "International Journal of Ecology \& Development",
  year =         "2008",
  volume =       "10",
  number =       "S08",
  pages =        "67--76",
  month =        "Summer",
  keywords =     "genetic algorithms, genetic programming, Wave data,
                 wave mapping, geometric programming, neural networks",
  ISSN =         "0972-9984",
  ISSN =         "0973-7308",
  URL =          "http://www.ceser.in/ceserp/index.php/ijed/article/view/374",
  abstract =     "Satellites gather vast quantities of ocean wave data
                 worldwide and such measurements are available to ocean
                 scientists and engineers at low costs. However
                 corresponding information is more useful in deeper sea
                 with open or exposed locations rather than nearshore
                 locations involving complex bathymetric effects. The
                 technique based on the approach of Artificial Neural
                 Network (ANN) of Radial Basis Function (RBF) and
                 Feed-forward Back-propagation (FFBP) to map remote
                 sensed deep-water waves with coastal waves was
                 attempted by the authors in the past (Kalra et al
                 (2005, a, b)). This paper presents an application of a
                 relatively new soft computing tool called Genetic
                 Programming for this purpose. Significant wave heights
                 at a number of locations over a track parallel to the
                 coastline are used to estimate the significant wave
                 heights at a nearshore site. The success of the method
                 adopted was confirmed from the satisfactory error
                 measures it produced during the testing carried out
                 following the training. The results are also compared
                 with those derived using artificial neural networks
                 (ANN). In general it was found that the spatial mapping
                 of wave heights done by genetic programming rivals that
                 by ANN.",
  notes =        "Department of Civil Engineering, IIT Bombay

                 ISRO, Ahmedabad, 380 015, India",
}

Genetic Programming entries for Ruchi Kalra M C Deo Raj Kumar Vijay K Agarwal

Citations