Genetic Programming Prediction of Solar Activity

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

@InProceedings{Jagielski:2000:GPP,
  author =       "Romuald Jagielski",
  title =        "Genetic Programming Prediction of Solar Activity",
  booktitle =    "Intelligent Data Engineering and Automated Learning -
                 IDEAL 2000: Data Mining, Financial Engineering, and
                 Intelligent Agents",
  editor =       "Kwong Sak Leung and Lai-Wan Chan and Helen Meng",
  year =         "2000",
  series =       "Lecture Notes in Computer Science",
  volume =       "1983",
  pages =        "199--205",
  address =      "Shatin, N.T., Hong Kong, China",
  month =        "13-15 " # dec,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-41450-9",
  CODEN =        "LNCSD9",
  ISSN =         "0302-9743",
  bibdate =      "Tue Sep 10 19:08:58 MDT 2002",
  DOI =          "doi:10.1007/3-540-44491-2_30",
  acknowledgement = ack-nhfb,
  size =         "7 pages",
  abstract =     "For many practical applications, such as planning for
                 satellite orbits and space missions, it is important to
                 estimate the future values of the sunspot numbers.
                 There have been numerous methods used for this
                 particular case of time series prediction, including
                 recently neural networks. In this paper we present
                 genetic programming technique employed to sunspot
                 series prediction. The paper investigates practical
                 solutions and heuristics for an effective choice of
                 parameters and functions of genetic programming. The
                 results obtained expect the maximum in the current
                 cycle of the smoothed series monthly sunspot numbers is
                 $164 \pm 20$, and $162 \pm 20$ for the next cycle
                 maximum, at the 95% level of confidence. These results
                 are discussed and compared with other predictions.",
}

Genetic Programming entries for Romuald Jagielski

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