Douhe Reservoir Flood Forecasting Model Based on Data Mining Technology

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@Article{Ji201293,
  author =       "He Ji and Wang Songlin and Wu Qinglin and 
                 Chen Xiaonan",
  title =        "Douhe Reservoir Flood Forecasting Model Based on Data
                 Mining Technology",
  journal =      "Procedia Environmental Sciences",
  volume =       "12, Part A",
  pages =        "93--98",
  year =         "2012",
  note =         "2011 International Conference of Environmental Science
                 and Engineering",
  ISSN =         "1878-0296",
  DOI =          "doi:10.1016/j.proenv.2012.01.252",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1878029612002538",
  keywords =     "genetic algorithms, genetic programming, Hydrological
                 Forecasting, Data Mining Technology, Artificial Neural
                 Networks",
  abstract =     "Calculating flood based on rainfall is an important
                 part of hydrological forecast. However, due to the
                 diversity and complexity of factors affecting the
                 relationship between rainfall and runoffs, using the
                 perspective of mechanism to simulate the forming of
                 flood through rainfall is often difficult. In this
                 paper, flood forecast model is constructed based on
                 Artificial Neural Networks (ANN) and Genetic
                 Programming (GP), using actual data to mine the
                 relationship among rainfall, pre rain and net rain, to
                 avoid the flaws of constructing actual mathematical
                 expression in advance, and automatically search for
                 optimal structure. Practice has approved that applying
                 data mining technique on flood forecasting of Douhe
                 Reservoir is able to achieve outstanding results.",
}

Genetic Programming entries for He Ji Wang Songlin Wu Qinglin Chen Xiaonan

Citations