title: Prediction of SO2 levels using neural networks.
abstract: 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.
authors.affiliation: Department of Statistics and Operations Research, Faculty of Mathematics, University of Santiago de Compostela, Santiago, Spain. fdcastro@usc.es
authors.forename: Belén M
authors.initials: BM
authors.lastname: Fernández de Castro
authors.forename: José Manuel
authors.initials: JM
authors.lastname: Prada Sánchez
authors.forename: Wenceslao
authors.initials: W
authors.lastname: González Manteiga
authors.forename: Manuel
authors.initials: M
authors.lastname: Febrero Bande
authors.forename: José Luis
authors.initials: JL
authors.lastname: Bermúdez Cela
authors.forename: Juan José
authors.initials: JJ
authors.lastname: Hernández Fernández
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D005544:Forecasting; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D013458:Sulfur Dioxide / Q000032:analysis*
chemical_list: D000393:Air Pollutants; D013458:Sulfur Dioxide