Model-building with interpolated temporal data

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "R. I. (Bob) McKay and Hoang Tuan Hao and 
                 Naoki Mori and Nguyen Xuan Hoai and Daryl Essam",
  title =        "Model-building with interpolated temporal data",
  journal =      "Ecological Informics",
  year =         "2006",
  volume =       "1",
  number =       "3",
  pages =        "259--268",
  month =        nov,
  note =         "4th International Conference on Ecological
  keywords =     "genetic algorithms, genetic programming, Linear
                 interpolation, Modelling",
  ISSN =         "1574-9541",
  URL =          "",
  DOI =          "doi:10.1016/j.ecoinf.2006.02.005",
  size =         "31 pages",
  abstract =     "Ecological data can be difficult to collect, and as a
                 result, some important temporal ecological datasets
                 contain irregularly sampled data. Since many temporal
                 modelling techniques require regularly spaced data, one
                 common approach is to linearly interpolate the data,
                 and build a model from the interpolated data. However,
                 this process introduces an unquantified risk that the
                 data is over-fitted to the interpolated (and hence more
                 typical) instances. Using one such irregularly-sampled
                 dataset, the Lake Kasumigaura algal dataset, we compare
                 models built on the original sample data, and on the
                 interpolated data, to evaluate the risk of mis-fitting
                 based on the interpolated data.",
  notes =        "",

Genetic Programming entries for R I (Bob) McKay Tuan-Hao Hoang Naoki Mori Nguyen Xuan Hoai Daryl Essam