Predictive function and rules for population dynamics of Microcystis aeruginosa in the regulated Nakdong River (South Korea), discovered by evolutionary algorithms

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@Article{Kim:2007:EM,
  author =       "Dong-Kyun Kim and Hongqing Cao and 
                 Kwang-Seuk Jeong and Friedrich Recknagel and Gea-Jae Joo",
  title =        "Predictive function and rules for population dynamics
                 of Microcystis aeruginosa in the regulated Nakdong
                 River (South Korea), discovered by evolutionary
                 algorithms",
  journal =      "Ecological Modelling",
  year =         "2007",
  volume =       "203",
  number =       "1-2",
  pages =        "147--156",
  month =        "24 " # apr,
  note =         "Special Issue on Ecological Informatics:
                 Biologically-Inspired Machine Learning, 4th Conference
                 of the International Society for Ecological
                 Informatics",
  keywords =     "genetic algorithms, genetic programming, Machine
                 learning, Regulated river, Evolutionary computation,
                 Algebraic function model, Rule-based model, Microcystis
                 aeruginosa, Sensitivity analysis",
  DOI =          "doi:10.1016/j.ecolmodel.2006.03.040",
  abstract =     "Two algorithms of evolutionary computation, an
                 algebraic function model and a rule-based model, were
                 applied for model development with respect to 8 years
                 of limnological data from the lower Nakdong River. The
                 aim of the modelling was to reproduce the abundances of
                 the phytoplankton species, Microcystis aeruginosa,
                 based on physical, chemical and meteorological
                 parameters. The algebraic function model overestimated
                 or underestimated abundance values, but correctly
                 recognised the timing of high abundances. The
                 rule-based model detected not only the timing of algal
                 blooms well but also the magnitude of abundances.
                 Sensitivity analysis indicates that high water
                 temperature influences high abundances of M. aruginosa.
                 In addition, dissolved oxygen, pH, nitrate and
                 phosphate are shown to be explainable in relation to
                 deoxygeneration, carbon dioxide transformation and
                 nutrient limitations.",
  notes =        "a Department of Biology, Pusan National University,
                 Jang-Jeon Dong, Gum-Jeong Gu, Busan 609-735, South
                 Korea

                 b School of Earth and Environmental Sciences,
                 University of Adelaide, SA 5005, Australia",
}

Genetic Programming entries for Dong-Kyun Kim Hong-Qing Cao Kwang-Seuk Jeong Friedrich Recknagel Gea-Jae Joo

Citations