The use of multilayer perceptrons for statistical modeling SO_2 non linear time series in Salta Capital, Argentina

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 behavi...

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Autores Principales: Musso, Haydeé Elena, Ávila Blas, Orlando José
Formato: Artículo
Idioma: Español
Publicado: 2015
Acceso en línea: http://revistas.ucr.ac.cr/index.php/matematica/article/view/8479
http://hdl.handle.net/10669/13026
Sumario: 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). Aneffective solution which uses multistep perceptrons theory was found. By using structural time series modelling, this solution is presentedby an iterative mathematical process that allows us to obtain a finalmodel with a high confidence level (95%) in order to do thefore casting step on the studied variable.