Optimal functional forms for estimation of missing precipitation data

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@Article{Teegavarapu2009106,
  author =       "Ramesh S. V. Teegavarapu and Mohammad Tufail and 
                 Lindell Ormsbee",
  title =        "Optimal functional forms for estimation of missing
                 precipitation data",
  journal =      "Journal of Hydrology",
  volume =       "374",
  number =       "1-2",
  pages =        "106--115",
  year =         "2009",
  ISSN =         "0022-1694",
  DOI =          "doi:10.1016/j.jhydrol.2009.06.014",
  URL =          "http://www.sciencedirect.com/science/article/B6V6C-4WH8CFX-4/2/2dc8195d13308dffa2798503d7038279",
  keywords =     "genetic algorithms, genetic programming, Missing
                 precipitation data, Spatial interpolation, Distance
                 weighting methods, Fixed function set genetic algorithm
                 method, Optimal functional forms",
  abstract =     "A fixed functional set genetic algorithm method
                 (FFSGAM) is proposed and is investigated in the current
                 study to obtain optimal functional forms for estimating
                 missing precipitation data. The FFSGAM provides
                 functional forms with optimal combination of parameters
                 of surrogate and actual measures of strength of
                 correlation among observations for estimating missing
                 data. The method uses genetic algorithms and a
                 nonlinear optimisation formulation to obtain optimal
                 functional forms and coefficients, respectively.
                 Historical daily precipitation data available from 15
                 rain gauge stations from the state of Kentucky, USA,
                 are used to test the functional forms and derive
                 conclusions about the efficacy of the proposed method
                 for estimating missing precipitation data. The tests of
                 FFSGAM at two rainfall gaging stations in Kentucky,
                 using multiple error and performance indices, indicate
                 that better estimates of precipitation can be obtained
                 compared to those from a traditional inverse distance
                 weighting technique. Also, results from the use of the
                 method confirm its robustness when only six rain gaging
                 stations out of 14 were used for estimating missing
                 data.",
  notes =        "GA used to evolve mathematical formulae",
}

Genetic Programming entries for Ramesh S V Teegavarapu Mohammad Tufail Lindell Ormsbee

Citations