Evaluating the Feasibility of Grammar-based GP in Combining Meteorological Forecast Models
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Dufek:2013:CEC,
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article_id = "1611",
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author = "Amanda Sabatini Dufek and Douglas Adriano Augusto and
Pedro Leite {da Silva Dias} and
Helio Jose Correa Barbosa",
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title = "Evaluating the Feasibility of Grammar-based GP in
Combining Meteorological Forecast Models",
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booktitle = "2013 IEEE Conference on Evolutionary Computation",
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volume = "1",
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year = "2013",
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month = jun # " 20-23",
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editor = "Luis Gerardo {de la Fraga}",
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pages = "32--39",
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address = "Cancun, Mexico",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution",
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isbn13 = "978-1-4799-0453-2",
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DOI = "doi:10.1109/CEC.2013.6557550",
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size = "7 pages",
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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.",
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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