Chaos in Nitrogen Dioxide Concentration Time Series and Its Prediction

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 289)

Abstract

This paper is aimed at analysis of Nitrogen Dioxide (NO2) concentration time series. At first we will estimate the time delay and the embedding dimension, which is needed for the Lyapunov exponent estimation and for the phase space reconstruction. Subsequently we will compute the largest Lyapunov exponent, which is one of the important indicators of chaos. Then we will calculate the 0-1 test for chaos. Finally we will compute predictions using a radial basis function to fit global nonlinear functions to the data. The results indicated that chaotic behaviors obviously exist in NO2 concentration time series.

Keywords

Chaos theory Nitrogen dioxide Time series analysis Phase space reconstruction Prediction Gaussian radial basis function 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.University of PardubicePardubiceCzech Republic

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