TY - JOUR
T1 - Pollutants time-series prediction using the gamma classifier
AU - López-Yáñez, Itzamá
AU - Argüelles-Cruz, Amadeo J.
AU - Camacho-Nieto, Oscar
AU - Yáñez-Márquez, Cornelio
N1 - Funding Information:
The authors would like to thank the Instituto Politécnico Nacional (Secretaría Académica, COFAA, SIP, and CIC), the CONACyT, SNI, and the ICyTDF (grants PIUTE10-77 and PICSO10-85) for their economical support to develop this work.
PY - 2011/6
Y1 - 2011/6
N2 - 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.
AB - 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.
KW - Associative models
KW - Environmental data prediction
KW - Gamma classifier
KW - Pattern classifier
KW - Time series prediction
UR - http://www.scopus.com/inward/record.url?scp=80052144517&partnerID=8YFLogxK
U2 - 10.1080/18756891.2011.9727822
DO - 10.1080/18756891.2011.9727822
M3 - Artículo
SN - 1875-6891
VL - 4
SP - 680
EP - 711
JO - International Journal of Computational Intelligence Systems
JF - International Journal of Computational Intelligence Systems
IS - 4
ER -