Genetic programming for spatiotemporal forecasting of housing prices

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

@InCollection{Kaboudan:2006:nicem,
  author =       "Mak Kaboudan",
  title =        "Genetic programming for spatiotemporal forecasting of
                 housing prices",
  booktitle =    "Handbook of Research on Nature-Inspired Computing for
                 Economics and Management",
  editor =       "Jean-Philippe Rennard",
  publisher =    "Idea Group Inc.",
  year =         "2007",
  volume =       "II",
  chapter =      "LV",
  pages =        "851--868",
  address =      "1200 E. Colton Ave",
  email =        "Mak_kaboudan@Redlands.edu",
  keywords =     "genetic algorithms, genetic programming, ANN, TSGP,
                 C++,",
  ISBN =         "1-59140-984-5",
  DOI =          "doi:10.4018/978-1-59140-984-7.ch055",
  abstract =     "This chapter compares forecasts of the median
                 neighbourhood prices of residential single-family homes
                 in Cambridge, Massachusetts, using parametric and
                 nonparametric techniques. Prices are measured over time
                 (annually) and over space (by neighborhood). Modelling
                 variables characterised by space and time dynamics is
                 challenging. Multi-dimensional complexities due to
                 specification, aggregation, and measurement errors
                 thwart use of parametric modeling, and nonparametric
                 computational techniques (specifically genetic
                 programming and neural networks) may have the
                 advantage. To demonstrate their efficacy, forecasts of
                 the median prices are first obtained using a standard
                 statistical method: weighted least squares. Genetic
                 programming and neural networks are then used to
                 produce two other forecasts. Variables used in
                 modelling neighbourhood median home prices include
                 economic variables such as neighbourhood median income
                 and mortgage rate, as well as spatial variables that
                 quantify location. Two years out-of-sample forecasts
                 comparisons of median prices suggest that genetic
                 programming may have the edge.",
  size =         "18 pages",
}

Genetic Programming entries for Mahmoud A Kaboudan

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