• DocumentCode
    1662289
  • Title

    A neural network model for rainfall estimation

  • Author

    McCullagh, J. ; Bluff, K. ; Ebert, E.

  • Author_Institution
    Dept. of Inf. Technol., Latrobe Univ., Bendigo, Australia
  • fYear
    1995
  • Firstpage
    389
  • Lastpage
    392
  • Abstract
    This paper investigates the use of an artificial neural network (ANN) to estimate the six hour rainfall over the south-east coast of Tasmania. ANNs are becoming increasingly prominent in many areas of weather forecasting due to their potential to capture the complex relationships between the many factors that contribute to certain weather conditions. The estimations produced by the ANNs were compared to one estimation technique and one forecasting technique used by the Bureau of Meteorology. The results confirm that ANNs have the potential for successful application to the problem of rainfall estimation
  • Keywords
    backpropagation; geophysics computing; neural nets; rain; weather forecasting; Bureau of Meteorology; Tasmania; artificial neural network; backpropagation; estimation technique; forecasting technique; neural network model; rainfall estimation; weather forecasting; Artificial neural networks; Atmosphere; Atmospheric modeling; Australia; Meteorology; Neural networks; Predictive models; Satellites; Temperature; Weather forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Neural Networks and Expert Systems, 1995. Proceedings., Second New Zealand International Two-Stream Conference on
  • Conference_Location
    Dunedin
  • Print_ISBN
    0-8186-7174-2
  • Type

    conf

  • DOI
    10.1109/ANNES.1995.499515
  • Filename
    499515