Prediction of inflows from dam catchment using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  title =        "Prediction of inflows from dam catchment using genetic
  author =       "Md Atiquzzaman and Jaya Kandasamy",
  journal =      "International Journal of Hydrology Science and
  year =         "2016",
  month =        mar # "~28",
  volume =       "6",
  number =       "2",
  pages =        "103--117",
  keywords =     "genetic algorithms, genetic programming, MIKE11-NAM,
                 hydroinformatics, climate scenarios, forecasting,
                 hydrology, rainfall prediction, inflows, inflow
                 prediction, catchment runoff, dam catchment, water
                 management, water resources, Australia, flow
  publisher =    "Inderscience Publishers",
  ISSN =         "2042-7816",
  bibsource =    "OAI-PMH server at",
  language =     "eng",
  rights =       "Inderscience Copyright",
  URL =          "",
  DOI =          "doi:10.1504/IJHST.2016.075560",
  abstract =     "Application of hydroinformatics tools for managing
                 water resources is common in the water industry. Over
                 the last few decades, several hydroinformatics tools
                 including genetic programming (GP) have been developed
                 and applied in hydrology. GP has been successfully
                 applied for calibration of numerous event-based
                 rainfall and runoff models. However, applying GP to
                 predict long-term time series for the management of
                 water resources is limited. This study demonstrates
                 GP's application in long-term prediction of catchment
                 runoff concerning a dam located in Oberon, New South
                 Wales, Australia. The calibration showed excellent
                 agreement between the observed and simulated flows
                 recorded over 30 years. The model was then applied for
                 the assessment of catchment yields for a future 100
                 years flows based on two assumed climatic scenarios.",

Genetic Programming entries for Md Atiquzzaman Jaya Kandasamy