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Local Model of the Air Quality on the Basis of Rough Sets Theory

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Soft Computing Models in Industrial and Environmental Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 188))

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Abstract

This article deals with the air quality modelling in two selected localities in the Czech Republic (CR). Data for the modelling were gained from the public sources. Primary source was the data server Czech Hydro Meteorological Institute (CHMI). Rough set theory (RST), Decision Trees (DTs) and Neutral Networks (NNs) were used for the analysis and the results comparison. At the end of the article there is the possible usage of the outputs of the models described. Outputs can help with the health protection of the inhabitants through the regulations set by the public administration authorities.

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Author information

Authors and Affiliations

  1. Institute of System Engineering and Informatics, Faculty of Economics and Administration, University of Pardubice, Studentská 84, 532 10, Pardubice, Czech Republic

    Filip Mezera & Jiří Křupka

Authors
  1. Filip Mezera
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  2. Jiří Křupka
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Corresponding author

Correspondence to Filip Mezera .

Editor information

Editors and Affiliations

  1. VŠB-TU Ostrava, 17. listopadu 15, Ostrava, 70833, Czech Republic

    Václav Snášel

  2. (MIR Labs), Scientific Network for Innovation and, Machine Intelligence Research Labs, Auburn, 98071-2259, Washington, USA

    Ajith Abraham

  3. , Dept. de Informática y Automática, University of Salamanca, Plaza de la Merced, s/n, Salamanca, 37008, Spain

    Emilio S. Corchado

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Mezera, F., Křupka, J. (2013). Local Model of the Air Quality on the Basis of Rough Sets Theory. In: Snášel, V., Abraham, A., Corchado, E. (eds) Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing, vol 188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32922-7_29

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  • DOI: https://doi.org/10.1007/978-3-642-32922-7_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32921-0

  • Online ISBN: 978-3-642-32922-7

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