Soft computing approach for real-time estimation of missing wave heights

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

@Article{Londhe20081080,
  author =       "S. N. Londhe",
  title =        "Soft computing approach for real-time estimation of
                 missing wave heights",
  journal =      "Ocean Engineering",
  volume =       "35",
  number =       "11-12",
  pages =        "1080--1089",
  year =         "2008",
  ISSN =         "0029-8018",
  DOI =          "doi:10.1016/j.oceaneng.2008.05.003",
  URL =          "http://www.sciencedirect.com/science/article/B6V4F-4SK633V-1/2/22702929635b97a45da2f5fbba866111",
  keywords =     "genetic algorithms, genetic programming, Water waves,
                 Buoy systems, Soft computing, Artificial Neural
                 Network, Missing data",
  abstract =     "This paper presents soft computing approach for
                 estimation of missing wave heights at a particular
                 location on a real-time basis using wave heights at
                 other locations. Six such buoy networks are developed
                 in Eastern Gulf of Mexico using soft computing
                 techniques of Artificial Neural Networks (ANN) and
                 Genetic Programming (GP). Wave heights at five stations
                 are used to estimate wave height at the sixth station.
                 Though ANN is now an established tool in time series
                 analysis, use of GP in the field of time series
                 forecasting/analysis particularly in the area of Ocean
                 Engineering is relatively new and needs to be explored
                 further. Both ANN and GP approach perform well in terms
                 of accuracy of estimation as evident from values of
                 various statistical parameters employed. The GP models
                 work better in case of extreme events. Results of both
                 approaches are also compared with the performance of
                 large-scale continuous wave modeling/forecasting system
                 WAVEWATCH III. The models are also applied on real time
                 basis for 3 months in the year 2007. A software is
                 developed using evolved GP codes (C++) as back end with
                 Visual Basic as the Front End tool for real-time
                 application of wave estimation model.",
  notes =        "See also \cite{Alavi20101239}",
}

Genetic Programming entries for S N Londhe

Citations