Prediction of SO2 levels using neural networks.
In this paper, we present an adaptation of the air pollution control help system in the neighborhood of a power plant in As Pontes (A Coruña, Spain), property of Endesa Generación S.A., to the European Council Directive 1999/30/CE. This system contains a statistic prediction made half an hour before the measurement, and it helps the staff in the power plant prevent air quality level episodes. The prediction is made using neural network models. This prediction is compared with one made by a semiparametric model.
Fernández de Castro
Belén M
BM
Department of Statistics and Operations Research, Faculty of Mathematics, University of Santiago de Compostela, Santiago, Spain. fdcastro@usc.es
Prada Sánchez
José Manuel
JM
González Manteiga
Wenceslao
W
Febrero Bande
Manuel
M
Bermúdez Cela
José Luis
JL
Hernández Fernández
Juan José
JJ
D000393:Air Pollutants / Q000032:analysis*; D005544:Forecasting; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D013458:Sulfur Dioxide / Q000032:analysis*
D000393:Air Pollutants; D013458:Sulfur Dioxide