The use of multilayer perceptrons for statistical modeling SO2 non linear time series in Salta Capital, Argentina

 

Αποθηκεύτηκε σε:
Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφείς: Musso, Haydeé Elena, Ávila Blas, Orlando José
Μορφή: artículo original
Κατάσταση:Versión publicada
Ημερομηνία έκδοσης:2013
Περιγραφή: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.
Χώρα:Portal de Revistas UCR
Ίδρυμα:Universidad de Costa Rica
Repositorio:Portal de Revistas UCR
Γλώσσα:Español
OAI Identifier:oai:portal.ucr.ac.cr:article/8479
Διαθέσιμο Online:https://revistas.ucr.ac.cr/index.php/matematica/article/view/8479
Λέξη-Κλειδί :time series
modelling
multistep perceptrons
air pollution
sulfure dioxide
passive sampling
series de tiempo
modelización
perceptrones multicapa
contaminación ambiental
dióxido de azufre
muestreo pasivo