Introducing knowledge into learning based on genetic programming

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@Article{Babovic:2009:JH,
  author =       "Vladan Babovic",
  title =        "Introducing knowledge into learning based on genetic
                 programming",
  journal =      "Journal of Hydroinformatics",
  year =         "2009",
  volume =       "11",
  number =       "3-4",
  pages =        "181--193",
  keywords =     "genetic algorithms, genetic programming, empirical
                 equations, hydraulics, sediment transport, strong
                 typing, symbolic regression, units of measurement",
  ISSN =         "1464-7141",
  URL =          "http://www.iwaponline.com/jh/011/0181/0110181.pdf",
  DOI =          "doi:10.2166/hydro.2009.041",
  size =         "13 pages",
  abstract =     "This work examines various methods for creating
                 empirical equations on the basis of data while taking
                 advantage of knowledge about the problem domain. It is
                 demonstrated that the use of high level concepts aid in
                 evolving equations that are easier to interpret by
                 domain specialists. The application of the approach to
                 real-world problems reveals that the use of such
                 concepts results in equations with performance equal or
                 superior to that of human experts. Finally, it is
                 argued that the algorithm is best used as a hypothesis
                 generator assisting scientists in the discovery
                 process.",
}

Genetic Programming entries for Vladan Babovic

Citations