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The Prediction of Tropospheric Ozone Using a Radial Basis Function Network

  • Kříž RadkoEmail author
  • Šedek Pavel
Part of the Emergence, Complexity and Computation book series (ECC, volume 14)

Abstract

The goal of this paper is to analyze the tropospheric ozone (O3) concentration time series and its prediction using artificial neural networks (ANNs). Tropospheric ozone has harmful effects on human health and on the environment. This study was based on daily averaged tropospheric ozone (O3) data from Pardubice in the Czech Republic. In this study, daily averaged ozone concentrations in Pardubice were predicted using a radial basis function network (RBFN) with three pollutant parameters and three meteorological factors in selected areas. We used a three-layer ANN, which consists of input, hidden, and output layers.

Keywords

Tropospheric ozone Time series analysis Artificial neural network Prediction Radial basis function network 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Faculty of Economics and Administration, Institute of Administrative and Social SciencesUniversity of PardubicePardubiceCzech Republic
  2. 2.Faculty of Electrical Engineering, Dept. of Economics, Management and HumanitiesCzech Technical UniversityPrahaCzech Republic

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