Citation
Vega Corona, Antonio and Barron Adame, Jose Miguel and Ibarra Manzano, Óscar Gerardo and Cortina Januchs, María Guadalupe and Quintanilla Domínguez, Joel and Andina de la Fuente, Diego
(2012).
Pollutant concentrations and Meteorological data classification by Neural Networks.
In: "World Automation Congress (WAC), 2012", 24/06/2012 - 28/06/2012, Puerto Vallarta (México). pp. 1-6.
Abstract
This paper present an environmental contingency forecasting tool based on Neural Networks (NN). Forecasting tool analyzes every hour and daily Sulphur Dioxide (SO2) concentrations and Meteorological data time series. Pollutant concentrations and meteorological variables are self-organized applying a Self-organizing Map (SOM) NN in different classes. Classes are used in training phase of a General Regression Neural Network (GRNN) classifier to provide an air quality forecast. In this case a time series set obtained from Environmental Monitoring Network (EMN) of the city of Salamanca, Guanajuato, México is used. Results verify the potential of this method versus other statistical classification methods and also variables correlation is solved.