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Modelling Air Pollution Time-Series by Using Wavelet Functions and Genetic Algorithms

  • G. Nunnari
  • L. Bertucco

Abstract

The peculiarity of the proposed approach is that of combining the use of wavelets and genetic algorithms for searching the best wavelets parameters in order to model a given pollution time series. The results are compared with a neural approach.

Keywords

Wavelet Function Learning Pattern Exogenous Input Meteorological Forecast International Data Exchange 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Wien 2001

Authors and Affiliations

  • G. Nunnari
  • L. Bertucco
    • 1
  1. 1.Dipartimento Elettrico Elettronico e SistemisticoUniversità degli Studi di CataniaCataniaItaly

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