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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Dufek:2013:CEC,

• 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 evolution",
• 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

Citations