A two-stage multi-agent system to predict the unsmoothed monthly sunspot numbers

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

@Article{Kaboudan:2009:ijamcs,
  author =       "Mak Kaboudan",
  title =        "A two-stage multi-agent system to predict the
                 unsmoothed monthly sunspot numbers",
  journal =      "International Journal of Mathematics and Computer
                 Sciences",
  year =         "2009",
  volume =       "5",
  number =       "3",
  pages =        "136--143",
  month =        "Summer",
  email =        "Mak_Kaboudan@Redlands.edu",
  keywords =     "genetic algorithms, genetic programming, Computational
                 techniques, discrete wavelet transformations, solar
                 cycle prediction, sunspot numbers",
  ISSN =         "2070-3902",
  URL =          "http://www.waset.org/journals/ijmcs/v5/v5-3-21.pdf",
  size =         "8 pages",
  abstract =     "A multi-agent system is developed here to predict
                 monthly details of the upcoming peak of the 24th solar
                 magnetic cycle. While studies typically predict the
                 timing and magnitude of cycle peaks using annual data,
                 this one uses the unsmoothed monthly sunspot number
                 instead. Monthly numbers display more pronounced
                 fluctuations during periods of strong solar magnetic
                 activity than the annual sunspot numbers. Because
                 strong magnetic activities may cause significant
                 economic damages, predicting monthly variations should
                 provide different and perhaps helpful information for
                 decision-making purposes. The multi-agent system
                 developed here operates in two stages. In the first, it
                 produces twelve predictions of the monthly numbers. In
                 the second, it uses those predictions to deliver a
                 final forecast. Acting as expert agents, genetic
                 programming and neural networks produce the twelve fits
                 and forecasts as well as the final forecast. According
                 to the results obtained, the next peak is predicted to
                 be 156 and is expected to occur in October 2011, with
                 an average of 136 for that year.",
}

Genetic Programming entries for Mahmoud A Kaboudan

Citations