• DocumentCode
    3509371
  • Title

    Application of artificial neural network to forecasting methods of time variation of the flow rate into a dam for a hydro-power plant

  • Author

    Ichiyanagi, K. ; Kobayashi, H. ; Matsumura, T. ; Kito, Y.

  • Author_Institution
    Dept. of Electr. Eng., Aichi Inst. of Technol., Toyota, Japan
  • fYear
    1993
  • fDate
    1993
  • Firstpage
    349
  • Lastpage
    354
  • Abstract
    This paper describes an attempt to apply a neural network method to forecast river flow rate following a fall of rain. The authors use a perceptron-type network comprised of three layers. The input data to the neural network are rainfall amounts and subsequent river flow rates. Further the predicted total volume and duration of the spell of rainfall in question are taken as additional input data. The output from the neural network is forecasted river flow rate. It is found from these investigations that the forecasting accuracy of the neural network is improved by utilization of the linear input-output relations of neurons.
  • Keywords
    dams; geophysics computing; hydroelectric power stations; hydrological techniques; neural nets; power engineering computing; rain; rivers; water supply; accuracy; artificial neural network; dam; hydroelectric power stations; hydrology; linear input-output relations; perceptron-type network; rain; river flow rate; three layers; Artificial neural networks; Computer networks; Gases; Load forecasting; Neural networks; Neurons; Rain; Rivers; Technology forecasting; Transfer functions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks to Power Systems, 1993. ANNPS '93., Proceedings of the Second International Forum on Applications of
  • Conference_Location
    Yokohama, Japan
  • Print_ISBN
    0-7803-1217-1
  • Type

    conf

  • DOI
    10.1109/ANN.1993.264323
  • Filename
    264323