Polluants Time-Series Prediction Using the Gamma Classifier

DOI

10.2991/ijcis.2011.4.4.23How to use a DOI?

Keywords

Gamma classifier, Time series prediction, Environmental data prediction, Pattern classifier, Associative models.

Abstract

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).

Copyright

© 2011, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Itzamá López-Yáñez
AU  - Amadeo J. Argüelles-Cruz
AU  - Oscar Camacho-Nieto
AU  - Cornelio Yáñez-Márquez
PY  - 2011
DA  - 2011/06/01
TI  - Polluants Time-Series Prediction Using the Gamma Classifier
JO  - International Journal of Computational Intelligence Systems
SP  - 680
EP  - 711
VL  - 4
IS  - 4
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.4.23
DO  - 10.2991/ijcis.2011.4.4.23
ID  - López-Yáñez2011
ER  -