Volume 4, Issue 4, June 2011, Pages 680 - 711
Polluants Time-Series Prediction Using the Gamma Classifier
Itzamá López-Yáñez, Amadeo J. Argüelles-Cruz, Oscar Camacho-Nieto, Cornelio Yáñez-Márquez
Received 20 September 2010, Accepted 2 May 2011, Available Online 1 June 2011.
- 10.2991/ijcis.2011.4.4.23How to use a DOI?
- Gamma classifier, Time series prediction, Environmental data prediction, Pattern classifier, Associative models.
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, 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/).
Cite this article
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 -