Infilling of Rainfall Information Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "C. Sivapragasam and Nitin Muttil and 
                 M. Catherin Jeselia and S. Visweshwaran",
  title =        "Infilling of Rainfall Information Using Genetic
  journal =      "Aquatic Procedia",
  volume =       "4",
  pages =        "1016--1022",
  year =         "2015",
  note =         "International conference on water resources, coastal
                 and ocean engineering, ICWRCOE'15",
  ISSN =         "2214-241X",
  DOI =          "doi:10.1016/j.aqpro.2015.02.128",
  URL =          "",
  abstract =     "The study suggests the use of Genetic Programming (GP)
                 based monthly model for infilling of missing rainfall
                 records in the rainfall time series for 3 rain gauge
                 stations in the Yarra River Basin in Australia from the
                 available rainfall information from the nearby
                 stations. This study compares simple linear model,
                 polynomial model, logarithmic model and a complex model
                 based on GP to infill the missing monthly rainfalls.
                 The RMSE and CC values of the validation data indicate
                 the potential of the suggested model. Further, it is
                 also interesting to note that GP evolved mathematical
                 models are able to predict the subtle inherent
                 non-linearity in the apparently predominantly linear
                 behaviour of the process.",
  keywords =     "genetic algorithms, genetic programming, infilling
                 rainfall, mathematical model, rain gauge stations",

Genetic Programming entries for C Sivapragasam Nitin Muttil M Catherin Jeselia S Visweshwaran