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Revista de Matemática Teoría y Aplicaciones
versión impresa ISSN 1409-2433
Resumen
MUSSO, Haydeé Elena y AVILA BLAS, Orlando José. The use of multilayer perceptrons for statistical modeling so2 non linear time series in Salta Capital, Argentina. Rev. Mat [online]. 2013, vol.20, n.1, pp.61-78. ISSN 1409-2433.
In this paper a statistical study of phisical-chemistry variables connected with enviroment pollution, specifically SO2 monthly average concentration, measured in Salta Capital city, Argentina, together with NO2 and O3 concentrations, was made. Time series under study shown non linear dinamic behaviour, outliers and structural changes. Due to these it was impossible to use typical econometric typologies (AR, MA, ARMA, ARIMA, among others). An effective solution which uses multistep perceptrons theory was found. By using structural time series modelling, this solution is presented by an iterative mathematical process that allows us to obtain a final model with a high confidence level (95%) in order to do the forecasting step on the studied variable.
Palabras clave : time series; modelling; multistep perceptrons; air pollution; sulfure dioxide; passive sampling.