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Revista de Matemática Teoría y Aplicaciones

Print version ISSN 1409-2433

Abstract

MUSSO, Haydeé Elena  and  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.

Keywords : time series; modelling; multistep perceptrons; air pollution; sulfure dioxide; passive sampling.

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