POLLUTANTS TIME-SERIES PREDICTION USING THE GAMMA CLASSIFIER
In this work we predict time series of air pollution data taken in Mexico City and the Valley of Mexico, by using the Gamma Classifier which is a novel intelligent associative mathematical model, coupled with an emergent coding technique. Historical and current data about the concentration of specific pollutants, in the form of time series, were used. The pollutants of interest are: carbon monoxide (CO), ozone (O-3), sulfur dioxide (SO2), and nitrogen oxides (NOx, including both nitrogen monoxide, NO, and nitrogen dioxide, NO2).
gamma classifier time series prediction environmental data prediction pattern classifier associative models