Pollutants time-series prediction using the gamma classifier

Research output: Contribution to journalArticle

20 Scopus citations


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 (O3), sulfur dioxide (SO2), and nitrogen oxides (NOx, including both nitrogen monoxide, NO, and nitrogen dioxide, NO2. © 2011 Taylor & Francis Group, LLC.
Original languageAmerican English
Pages (from-to)680-711
Number of pages608
JournalInternational Journal of Computational Intelligence Systems
StatePublished - 1 Jan 2011
Externally publishedYes


Cite this