Back to Search Start Over

Hourly Forecasting of SO2 Pollutant Concentration Using an Elman Neural Network.

Authors :
Apolloni, Bruno
Marinaro, Maria
Nicosia, Giuseppe
Tagliaferri, Roberto
Brunelli, U.
Piazza, V.
Pignato, L.
Sorbello, F.
Vitabile, S.
Source :
Neural Nets; 2006, p65-69, 5p
Publication Year :
2006

Abstract

In this paper the first results produced by an Elman neural network for hourly SO2 ground concentration forecasting are presented. Time series has been recorded between 1998 and 2001 and are referred to a monitoring station of SO2 in the industrial site of Priolo, Syracuse, Italy. Data has been kindly provided by CIPA (Consorzio Industriale per la Protezione dell'Ambiente, Siracusa, Italia). Time series parameters are the horizontal and vertical wind velocity, the wind direction, the stability classes of Thomas, the base level of the layer of the atmospheric stability, the gradient of the potential temperature and the difference of the potential temperature of reference. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540331834
Database :
Supplemental Index
Journal :
Neural Nets
Publication Type :
Book
Accession number :
32963306
Full Text :
https://doi.org/10.1007/11731177_10