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Neural Network Modelling: Perspectives of Application for Monitoring and Forecasting Physical-Chemical Variables in the Boundary Layer

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Part of the book series: NATO ASI Series ((ASEN,volume 8))

Abstract

The aim of this paper is to present environmental applications of a technique of neural network modelling, which demonstrates its usefulness in the simulation of real systems that are complex, time-changing and characterised by many feed-back processes, such as the atmospheric pollution environment.

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References

  • Allegrini I., Febo A., Pasini A, Schiarini S. (1994) Monitoring of the nocturnal mixed layer by means of particulate radon progeny measurement. J. Geophys. Res. 99 (D9), 18765–18777.

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  • Boznar M., Lesjak M., Mlakar P. (1994) A neural network based method for short-term predictions of ambient SO2 concentrations in highly polluted industrial areas of complex terrain. Atmos. Environ. (in press)

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  • Hertz J., Krough A., Palmer RG. (1991) Introduction to the theory of neural computation. Addison Wesley.

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  • Pasini A, Potestà S. Short-range visibility forecast by means of neural network modelling: a case study (in preparation)

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© 1996 Springer-Verlag Berlin Heidelberg

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Pasini, A., Potestà, S. (1996). Neural Network Modelling: Perspectives of Application for Monitoring and Forecasting Physical-Chemical Variables in the Boundary Layer. In: Allegrini, I., De Santis, F. (eds) Urban Air Pollution. NATO ASI Series, vol 8. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-61120-9_26

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  • DOI: https://doi.org/10.1007/978-3-642-61120-9_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-64703-1

  • Online ISBN: 978-3-642-61120-9

  • eBook Packages: Springer Book Archive

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