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Fuzzy Inference ANN Ensembles for Air Pollutants Modeling in a Major Urban Area: The Case of Athens

  • Ilias Bougoudis
  • Lazaros Iliadis
  • Antonis Papaleonidas
Part of the Communications in Computer and Information Science book series (CCIS, volume 459)

Abstract

All over the globe, major urban centers face a significant air pollution problem, which is becoming worse every year. This research effort aims to contribute towards real time monitoring of air quality, which is a target of great importance for people’s health. However, a serious obstacle is the high percentage of erroneous or missing data which is highly prolonged in many of the cases. To overcome this problem and due to the individuality of each residential area of Athens, separate local ANN had to be developed, capable of performing reliable interpolation of missing data vectors on an hourly basis. Also due to the need for hourly overall estimations of pollutants in the wider area of a major city, ANN ensembles were additionally developed by employing four existing methods and an innovative fuzzy inference approach.

Keywords

ANN ensembles Fuzzy Inference System Air Pollution 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ilias Bougoudis
    • 1
  • Lazaros Iliadis
    • 1
  • Antonis Papaleonidas
    • 1
  1. 1.Department of Forestry & Management of the Environment & Natural ResourcesDemocritus University of ThraceN OrestiadaGreece

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