• DocumentCode
    427475
  • Title

    Artificial neural networks for meteorological nowcast

  • Author

    Pasero, Eros ; Moniaci, Walter

  • fYear
    2004
  • fDate
    14-16 July 2004
  • Firstpage
    36
  • Lastpage
    39
  • Abstract
    Weather forecast are a typical problem where a huge amount of data coming from different types of sensors must be elaborated by means of complex, time-consuming algorithms. This work presents a new approach where the data fusion is performed with soft computing techniques. A statistical-neural system is used to "nowcast" meteorological data measured by a weather station. The system is able to forecast the evolution of these parameters in next three hours, giving precious indications about the possibility of rain, ice, and fog in next future.
  • Keywords
    geophysics computing; neural nets; sensor fusion; weather forecasting; artificial neural networks; data fusion; nowcast meteorological data; soft computing; statistical neural system; time consuming algorithm; weather forecast system; Artificial neural networks; Atmosphere; Atmospheric modeling; Ice; Meteorology; Optical computing; Predictive models; Roads; Snow; Weather forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Measurement Systems and Applications, 2004. CIMSA. 2004 IEEE International Conference on
  • Print_ISBN
    0-7803-8341-9
  • Type

    conf

  • DOI
    10.1109/CIMSA.2004.1397226
  • Filename
    1397226