Soft Computing Techniques Applied to a Case Study of Air Quality in Industrial Areas in the Czech Republic

  • Ángel Arroyo
  • Emilio Corchado
  • Verónica Tricio
  • Laura García-Hernández
  • Václav Snášel
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 188)

Abstract

This multidisciplinary research analyzes the atmospheric pollution conditions of two different places in Czech Republic. The case study is based on real data provided by the Czech Hydrometeorological Institute along the period between 2006 and 2010. Seven variables with atmospheric pollution information are considered. Different Soft Computing models are applied to reduce the dimensionality of this data set and show the variability of the atmospheric pollution conditions among the two places selected, as well as the significant variability of the air quality along the time.

Keywords

Artificial neural networks soft computing meteorology statistical models environmental conditions 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ángel Arroyo
    • 1
  • Emilio Corchado
    • 2
    • 5
    • 6
  • Verónica Tricio
    • 3
  • Laura García-Hernández
    • 4
  • Václav Snášel
    • 5
    • 6
  1. 1.Department of Civil EngineeringUniversity of BurgosBurgosSpain
  2. 2.Departmento de Informática y AutomáticaUniversity of SalamancaSalamancaSpain
  3. 3.Department of PhysicsUniversity of BurgosBurgosSpain
  4. 4.Area of Project EngineeringUniversity of CordobaCordobaSpain
  5. 5.Department of Computer ScienceVSB-Technical University of OstravaOstravaCzech Republic
  6. 6.IT4InnovationsOstravaCzech Republic

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