Induction of a marsupial density model using genetic programming and spatial relationships

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@Article{Whigham:2000:EM,
  author =       "P. A. Whigham",
  title =        "Induction of a marsupial density model using genetic
                 programming and spatial relationships",
  journal =      "Ecological Modelling",
  volume =       "131",
  pages =        "299--317",
  year =         "2000",
  number =       "2-3",
  keywords =     "genetic algorithms, genetic programming, Machine
                 learning, Spatial patterns, Habitat prediction",
  URL =          "http://www.sciencedirect.com/science/article/B6VBS-40V4BS0-F/2/e4af01a33144a2b89762925cc1c0722c",
  DOI =          "doi:10.1016/S0304-3800(00)00248-9",
  abstract =     "Machine learning techniques have been developed that
                 allow the induction of spatial models for the
                 prediction of habitat types and population
                 distribution. However, most learning approaches are
                 based on a propositional language for the development
                 of models and therefore cannot express a wide range of
                 possible spatial relationships that exist in the data.
                 This paper compares the application of a functional
                 evolutionary machine learning technique for prediction
                 of marsupial density to some standard machine learning
                 techniques. The ability of the learning system to
                 express spatial relationships allows an improved
                 predictive model to be developed, which is both
                 parsimonious and understandable. Additionally, the maps
                 produced from this approach have a generalised
                 appearance of the measured glider density, suggesting
                 that the underlying preferred habitat properties of the
                 greater glider have been identified.",
}

Genetic Programming entries for Peter Alexander Whigham

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