Neural Nets pp 95-104 | Cite as

Short Term Local Meteorological Forecasting Using Type-2 Fuzzy Systems

  • Arianna Mencattini
  • Marcello Salmeri
  • Stefano Bertazzoni
  • Roberto Lojacono
  • Eros Pasero
  • Walter Moniaci
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3931)


Meteorological forecasting is an important issue in research. Typically, the forecasting is performed at “global level,” by gathering data in a large geographical region and by studying their evolution, thus foreseeing the meteorological situation in a certain place. In this paper a “local level” approach, based on time series forecasting using Type-2 Fuzzy Systems, is proposed. In particular temperature forecasting is inspected. The Fuzzy System is trained by means of historical local time series. The algorithm uses a detrend procedure in order to extract the chaotic component to be predicted.


Membership Function Fuzzy Neural Network Fuzzy Logic System Time Series Forecast Time Series Prediction 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Arianna Mencattini
    • 1
  • Marcello Salmeri
    • 1
  • Stefano Bertazzoni
    • 1
  • Roberto Lojacono
    • 1
  • Eros Pasero
    • 2
  • Walter Moniaci
    • 2
  1. 1.Dip. Ingegneria ElettronicaUniversità di Roma “Tor Vergata”Roma RMItaly
  2. 2.Dip. Elettronica, Politecnico di TorinoTorino TOItaly

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