• DocumentCode
    3583989
  • Title

    Climate variables and future hydrological scenarios: understanding causes, predicting consequences

  • Author

    Szczupak, Jacques ; De Macedo, Luiz H. ; Sallas, Edgard ; Pinto, Leontina

  • Author_Institution
    Electr. Electron. Dept., PUC-RIO, Brazil
  • fYear
    2004
  • Firstpage
    386
  • Lastpage
    390
  • Abstract
    This work presents a new model for future hydrological inflow forecast. Instead of trying to repeat the past, the proposed approach targets the future prediction based on climatological information able to explain hydrological behavior of the desired variables. A neural network, customized to extract sensitive data information, "translates" climatological forecasts into future hydrological scenarios.
  • Keywords
    hydroelectric power stations; neural nets; power engineering computing; climatological forecast; hydroelectric power system; hydrological inflow forecast; hydrological scenarios; neural network; Contracts; Data mining; Floods; Hydroelectric power generation; Load forecasting; Neural networks; Portfolios; Predictive models; Student members; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems, 2004 International Conference on
  • Print_ISBN
    0-9761319-1-9
  • Type

    conf

  • Filename
    1378719