Estimation Models Generation using Linear Genetic Programming

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

@Article{MartinezCanillas:2009:CLEI,
  author =       "Javier {Martinez Canillas} and Roberto Sanchez and 
                 Benjamin Baran",
  title =        "Estimation Models Generation using Linear Genetic
                 Programming",
  journal =      "CLEI Electronic Journal",
  year =         "2009",
  volume =       "13",
  number =       "3",
  pages =        "paper 4",
  month =        dec,
  note =         "Regular Issue and Special Issue of Best Papers
                 presented at CLEI 2008, Santa Fe, Argentina",
  keywords =     "genetic algorithms, genetic programming, economic
                 indicators, time series, forecasting",
  ISSN =         "0717-5000",
  URL =          "http://www.clei.cl/cleiej/papers/v12i3p4.pdf",
  URL =          "http://www.clei.cl/cleiej/paper.php?id=172",
  size =         "8 pages",
  abstract =     "he use of decision rules and estimation techniques is
                 increasingly common for decision making. In recent
                 years studies were conducted which applies Genetic
                 Programming (GP) to obtain rules to make predictions. A
                 new branch in the area of Evolutionary Algorithms (EA)
                 is Linear Genetic Programming (LGP). LGP evolves
                 instructions sequences of an imperative programming
                 language. This paper proposes estimation models
                 generation for time series forecasting using LGP. The
                 forecasting result for the Consumer Price Index (CPI)
                 and the price of soybeans per ton shows the potential
                 of this new proposal.

                 Spanish Abstract:

                 El uso de reglas de decision y tecnicas de estimacion
                 es cada vez mas coman para la toma de decisiones.
                 Recientemente se han hecho estudios usando programacion
                 genetica para obtener reglas que hagan predicciones.
                 Una area novedosa dentro de los algoritmos evolutivos
                 es la programacion genetica lineal (LGP). LGP
                 evoluciona secuencias de instrucciones de un lenguaje
                 imperativo. Este trabajo propone generar modelos de
                 estimacion para la prediccion de series de tiempo
                 usando LGP. El resultado de la prediccion para el
                 indice de precios al consumidor y el precio de la soja
                 por tonelada muestra el potencial de esta propuesta.",
  notes =        "CLEI (Latin-american Center for Informatics Studies)
                 http://www.clei.cl/cleiej/index.html",
}

Genetic Programming entries for Javier Martinez Canillas Roberto Sanchez Benjamin Baran Cegla

Citations