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Technical Paper

Systematic Development of an Artificial Neural Network Model for Real-Time Prediction of Ground-Level Ozone in Edmonton, Alberta, Canada

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Pages 1847-1857 | Published online: 01 Mar 2012

References

  • Jain, A.K.; Mao, J;. Mohiuddin, K.M. Artificial Neural Networks: A Tutorial; Computer 1996, 3, 31-44.
  • El-Din, A.; Smith, D.W.A. Neural Network Model to Predict the Wastewater Inflow Incorporating Rainfall Events; Wat. Res. 2002, 36, 1115-1126.
  • Flood, I.; Kartam, N. In Artificial Neural Networks for Civil Engineers: Fundamentals and Applications; Kartam, N.; Flood, I.; Garrett, J.H., Jr., Eds.; American Society of Civil Engineers: New York, 1997; pp 19-43.
  • Garrett, J.H., Jr.; Gunaratman, D.J.; Ivezic, N. In Artificial Neural Networks for Civil Engineers: Fundamentals and Applications; Kartam, N.; Flood, I.; Garrett, J.H., Jr., Eds.; American Society of Civil Engineers: New York, 1997; pp 1-18.
  • Henseler, J. In Artificial Neural Networks; An Introduction to ANN Theory and Practice; Braspenning, P.J.; Thuijsman, F.;Weijters, A.J.M.M., Eds.; Springer-Verlag: Berlin, Germany, 1995; pp 37-66.
  • Greig, A.J.; Cawley, G.; Dorling, S.; Eben, K.; Fiala, A.J.; Karppinen, A.; Keder, J.; Kolehmainen, M.; Kukkonen, K.; Libero, B.; Macoun, J.; Niranjan, M.; Nucifora, A.; Nunnari, A.; Palus, M.; Pelikan, E.; Ruuskanen, J.; Schlink, U. Air Pollution Episodes: Modeling Tools for Improved mog Management (APPETISE). In Proceedings of the Eighth International Conference on Air Pollution, New Hall College, Cambridge University, 2000; WIT Press: Southampton, England, 2000; pp 89-98.
  • Burrascano, P. Neural Networks for Environmental Data Processing: A Research Project of Relevant National Interest for the Italian Government; Int. J. Appl. Electrom. 2001/2002, 13, 3-11.
  • Seinfeld, J.H. Atmospheric Chemistry and Physics of Air Pollution; Wiley: New York, NY, 1986.
  • Jacobson, M. Z. Fundamentals of Atmospheric Modeling; Cambridge University Press: Cambridge, United Kingdom, 1999.
  • Sandhu, H.S. Ground-Level O3 in Alberta; Science and Technology Branch, Environmental Sciences Division, Alberta Environmental Protection: Edmonton, Alberta, Canada, 1999.
  • McElroy, M. B. The Atmospheric Environment: Effects of Human Activity; Princeton University Press: Princeton, NJ and Oxford, United Kingdom, 2002.
  • Potter, T. D.; Colman, B. R. Handbook of Weather, Climate, and Water: Chemistry, Hydrology, and Societal Impacts; John Wiley and Sons, Inc.: Hoboken, NJ, 2003.
  • Comrie, A.C. Comparing Neural Networks and Regression Models for O3 Forecasting; J. Air & Waste Manage. Assoc. 1997, 47, 653-663.
  • Jorquera, H.; Perez, R.; Cipriano, A.; Espejo, A.; Letelier, M.V.; Acuna, G. Forecasting O3 Daily Maximum Levels at Santiago, Chile; Atmos. Environ. 1998, 32, 3415-3424.
  • Nunnari, G.; Nucifora, A.F.M.; Randieri, C. The Application of Neural Techniques to the Modeling of Time-Series of Atmospheric Pollution Data. Ecol. Model. 1998, 111, 187-205.
  • Garson, G.D. Interpreting Neural-Network Connection Weights; AI Expert 1991, 4, 47-51.
  • Cannon, A.J.; Lord, E.R. Forecasting Summertime Surface-Level O3 Concentrations in the Lower Fraser Valley of British Columbia: An Ensemble Neural Network Approach; J. Air & Waste Manage. Assoc. 2000, 50, 322-339.
  • Yi, J.; Prybutok, V.R. A Neural Network Model Forecasting for Prediction of Daily Maximum O3 Concentration in an Industrialized Urban Area; Environ. Pollut. 1996, 92, 349-357.
  • Spellman, G. an Application of Artificial Neural Networks to the Prediction of Surface O3 Concentrations in the United Kingdom; Appl. Geogr. 1999, 19, 123-136.
  • Hasham, F.A. M.Sc. Thesis, University of Alberta, Alberta, Canada, 1998.
  • Benkley, C.W.; Schulman, L.L. Estimating Hourly Mixing Depths From Historical Meteorological Data; J. Appl. Meteorol. 1979, 6, 772-780.
  • Cox, W.M. Protocol for Determining the Best Performing Model; U.S. Environmental Protection Agency Office of Air Quality Planning and Standards, Technical Support Division, Source Receptor Analysis Branch: Research Triangle Park, NC, 1988.
  • Walpole, R.E.; Myers, R.H. Probability and Statistics for Engineers and Scientists, 5th Ed.; Macmillan Publishing Company: New York, 1993.
  • Ruiz-Suarez, J.C.; Mayora-Ibarra, O.A.; Torres-Jimenez, J.; Ruiz-Suarez, L.G. Short-Term O3 Forecasting by Artificial Neural Networks; Adv. Eng. Softw. 1995, 23, 143-149.
  • Abdul-Wahab, S.A.; Al-Alawi, S.M. Assessment and Prediction of Tropospheric O3 Concentration Levels Using Artificial Neural Networks; Environ. Modell. Softw. 2002, 17, 219-228.
  • Canadian Environmental Protection Act Federal/Provincial Working Group on Air Quality Objectives and Guidelines. National Ambient Air Quality Objectives for Ground-Level O3 Science Assessment Document, Catalogue No. En42–17/702–1999E; Health Canada and Environment Canada: Downsview and Ottawa, Canada, 1999.
  • Chaikowsky, C.L.A. Overview of Ground-Level O3 Observations in Alberta, 1986–1998; Science and Technology Branch, Environmental Sciences Division, Alberta Environmental Protection: Edmonton, Alberta, Canada, 2001.
  • Cheng, L.; McDonald, K.M.; Angle, R.P.; Sandhu, H.S. Forest Fire Enhanced Photochemical Air Pollution. A Case Study; Atmos. Environ. A-Gen. 1998, 32, 673-681.

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