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Predicting Daily Average SO2 Concentrations in the Industrial Area of Syracuse (Italy)

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Artificial Neural Nets and Genetic Algorithms

Abstract

In this paper artificial neural networks are used to build 1- day-ahead SO2 prediction models. The structure of the model was obtained following appropriate statistical analysis of the time series.

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References

  1. Holland D. M., Principe P. P., Sickles J. E.: Trends in atmospheric sulfur and nitrogen species in the eastern United States for 1989-1995. Atmospheric Environment 33, pp. 37–49 (1999).

    Google Scholar 

  2. Zannetti P.: Air Pollution Modeling, Theories, Computational Methods and A vailable Software Ed. Van Nostrand Reinhold, New York, 1990.

    Google Scholar 

  3. Boznar M, Lesjak M., Mlakar P.: A Neural Network Based Method for Short-Terrn Predictions of Ambient SO2 Concentrations in Highly Polluted Industrial Areas of Complex Terrain. Atmospheric Environment, 27B, 2, pp. 221–230 (1993).

    Google Scholar 

  4. Nunnari G., Nucifora A., Randieri C.: The Application of Neural Techniques to the Modelling of Time Series of Atmospheric Pollution Data. Ecological Modelling, 111, pp. 187–205 (1998).

    Article  Google Scholar 

  5. Arena P., Baglio S., Castorina C., Fortuna L., Nunnari G.: A Neural Architecture to Predict Pollution in Industrial Areas. Proceedings of ICNN, 4, pp. 2107–2112, Washington (1996).

    Google Scholar 

  6. Van Aalst R. M., De Leeuw F. A. A. M. (editors), National Ozone Forecasting System and International Data Exchange in Northwest Europe, European Topic Centre on Air Quality, 1997.

    Google Scholar 

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© 2001 Springer-Verlag Wien

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Nunnari, G., Bertucco, L., Milio, D. (2001). Predicting Daily Average SO2 Concentrations in the Industrial Area of Syracuse (Italy). In: Kůrková, V., Neruda, R., Kárný, M., Steele, N.C. (eds) Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6230-9_123

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  • DOI: https://doi.org/10.1007/978-3-7091-6230-9_123

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83651-4

  • Online ISBN: 978-3-7091-6230-9

  • eBook Packages: Springer Book Archive

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