Process-based simulation library SALMO-OO for lake ecosystems. Part 2: Multi-objective parameter optimization by evolutionary algorithms

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@Article{Cao2008181,
  author =       "Hongqing Cao and Friedrich Recknagel and 
                 Lydia Cetin and Byron Zhang",
  title =        "Process-based simulation library SALMO-OO for lake
                 ecosystems. Part 2: Multi-objective parameter
                 optimization by evolutionary algorithms",
  journal =      "Ecological Informatics",
  volume =       "3",
  number =       "2",
  pages =        "181--190",
  year =         "2008",
  ISSN =         "1574-9541",
  DOI =          "doi:10.1016/j.ecoinf.2008.02.001",
  URL =          "http://www.sciencedirect.com/science/article/B7W63-4S69SG8-1/2/95e920ec339c554888f67696a93f2f37",
  keywords =     "genetic algorithms, genetic programming,
                 Multi-objective parameter optimization, SALMO-OO, Lake
                 categories, Evolutionary algorithms",
  abstract =     "SALMO-OO represents an object-oriented simulation
                 library for lake ecosystems that allows to determine
                 generic model structures for certain lake categories.
                 It is based on complex ordinary differential equations
                 that can be assembled by alternative process equations
                 for algal growth and grazing as well as zooplankton
                 growth and mortality. It requires 128 constant
                 parameters that are causally related to the metabolic,
                 chemical and transport processes in lakes either
                 estimated from laboratory and field experiments or
                 adopted from the literature. An evolutionary algorithm
                 (EA) was integrated into SALMO-OO in order to
                 facilitate multi-objective optimization for selected
                 parameters and to substitute them by optimum
                 temperature and phosphate functions. The parameters
                 were related to photosynthesis, respiration and grazing
                 of the three algal groups diatoms, green algae and
                 blue-green algae. The EA determined specific
                 temperature and phosphate functions for same parameters
                 for 3 lake categories that were validated by ecological
                 data of six lakes from Germany and South Africa.

                 The results of this study have demonstrated that: (1)
                 the hybridization of ordinary differential equations by
                 EA provide a sophisticated approach to fine-tune
                 crucial parameters of complex ecological models, and
                 (2) the multi-objective parameter optimization of
                 SALMO-OO by EA has significantly improved the accuracy
                 of simulation results for three different lake
                 categories.",
}

Genetic Programming entries for Hong-Qing Cao Friedrich Recknagel Lydia Cetin Byron He Zhang

Citations