Evaluating the Feasibility of Grammar-based GP in Combining Meteorological Forecast Models

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  article_id =   "1611",
  author =       "Amanda Sabatini Dufek and Douglas Adriano Augusto and 
                 Pedro Leite {da Silva Dias} and 
                 Helio Jose Correa Barbosa",
  title =        "Evaluating the Feasibility of Grammar-based GP in
                 Combining Meteorological Forecast Models",
  booktitle =    "2013 IEEE Conference on Evolutionary Computation",
  volume =       "1",
  year =         "2013",
  month =        jun # " 20-23",
  editor =       "Luis Gerardo {de la Fraga}",
  pages =        "32--39",
  address =      "Cancun, Mexico",
  keywords =     "genetic algorithms, genetic programming, grammatical
  isbn13 =       "978-1-4799-0453-2",
  DOI =          "doi:10.1109/CEC.2013.6557550",
  size =         "7 pages",
  abstract =     "The purpose of this paper is to evaluate the
                 feasibility of grammatical evolution (GE) in combining
                 meteorological models into more accurate single
                 forecast of rainfall amount. A set of GE experiments
                 was performed comparing six proposed ensemble forecast
                 grammars on three benchmark problems. We also proposed
                 a manner of designing benchmark problems by creating
                 arbitrary combinations of meteorological models, as
                 well as modelling the effect of weather patterns over
                 models as explicit functions. The results showed that
                 the GE algorithm obtained a superior performance
                 relative to three traditional statistical methods for
                 all the benchmark problems. A comparison among the
                 developed grammars showed that our most complex
                 grammar, which allows non-linear combinations of models
                 and an unrestricted use of patterns, turned out to be
                 the overall best performing proposal.",
  notes =        "CEC 2013 - A joint meeting of the IEEE, the EPS and
                 the IET.",

Genetic Programming entries for Amanda Sabatini Dufek Douglas A Augusto Pedro Leite da Silva Dias Helio J C Barbosa