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Nonlinearity and Prediction of Air Pollution

  • Milan Paluš
  • Emil Pelikán
  • Kryštof Eben
  • Pavel Krejčíř
  • Pavel Juruš

Abstract

A presence of nonlinearity in time series of concentrations of air pollutants and in their relations to time series of meteorological variables is tested using information-theoretic functionals and the surrogate data approach. The results are discussed in relation to predictability of the pollutant concentrations aimed to alert smog episodes.

Keywords

Mutual Information Diurnal Cycle Surrogate Data Instantaneous Amplitude Ground Level Ozone 
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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Copyright information

© Springer-Verlag Wien 2001

Authors and Affiliations

  • Milan Paluš
  • Emil Pelikán
  • Kryštof Eben
  • Pavel Krejčíř
  • Pavel Juruš
    • 1
  1. 1.Institute of Computer ScienceAcademy of Sciences of the Czech RepublicPrague 8Czech Republic

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