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Fuzzy Description of Air Quality: A Case Study

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 6954)


The methods suggested by US -EPA for computation of air quality indices do not include expert’s knowledge. There exists aleotary uncertainty in the pollution parametric data and the epistemic uncertainty in describing the pollutants by the domain experts in linguistic terms such as good, very good, etc. Fuzzy logic based formalism presented in this paper can model two types of uncertainties, and finally straightway describe air quality in linguistic terms with a degree of certainty attached to each term.

The case study relates to the assessment of the status of ambient air quality in Pune city at the defined air quality monitoring stations, using fuzzy logic based formalism. The comparison of the results obtained using the conventional method of computing air quality index and the proposed fuzzy logic based method is an integral part of the paper.


  • Air quality index
  • uncertainty
  • fuzzy rule based system
  • linguistic terms
  • bootstrap method
  • convex normalized fuzzy Number
  • degree of match
  • Degree of Certainty

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© 2011 Springer-Verlag Berlin Heidelberg

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Yadav, J.Y., Kharat, V., Deshpande, A. (2011). Fuzzy Description of Air Quality: A Case Study. In: Yao, J., Ramanna, S., Wang, G., Suraj, Z. (eds) Rough Sets and Knowledge Technology. RSKT 2011. Lecture Notes in Computer Science(), vol 6954. Springer, Berlin, Heidelberg.

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24424-7

  • Online ISBN: 978-3-642-24425-4

  • eBook Packages: Computer ScienceComputer Science (R0)