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Modeling vehicle air pollution attributes by artificial neural network

Vaziri, M ; Sharif University of Technology | 2001

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  1. Type of Document: Article
  2. Publisher: Sharif University of Technology , 2001
  3. Abstract:
  4. The municipalities of large Iranian cities require regular air pollutant emission monitoring for motor vehicles. The recorded data include information about commonly regulated air pollutants and motor vehicle characteristics which were randomly selected and studied from the Tehran database. Regression analysis was found ineffective in modeling the relationships among air pollutant, meteorological and motor vehicle characteristics. However, the artificial neural network, ANN, modeling seem to be a useful tool for prediction of air pollutants. The developed ANN models were found to be superior to the developed regression models. Application of the study approach and results could improve motor vehicle air quality monitoring and control activities for urban areas
  5. Keywords:
  7. Source: Scientia Iranica ; Volume 8, Issue 1 , 2001 , Pages 10-15 ; 10263098 (ISSN)
  8. URL: http://scientiairanica.sharif.edu/article_2777.html