TY - GEN
T1 - On trend association analysis of time series of atmospheric pollutants and meteorological variables in mexico city metropolitan area
AU - Almanza, Victor
AU - Batyrshin, Ildar
PY - 2011
Y1 - 2011
N2 - The paper studies trend associations between atmospheric pollutants and meteorological variables time series of Mexico City Metropolitan Area (MCMA) by applying the Moving Approximation Transform (MAP). This recently introduced technique measures and visualizes associations of the dynamics between different time series in the form of an association network. The paper studies associations between 5 atmospheric pollutants (SO2, O3, NO2, NOx and PM2.5) and 7 meteorological variables (mean wind velocity, minimum, average and maximum values of both temperature and relative humidity) measured daily during one year in three meteorological stations located in different zones of MCMA. These associations were studied for 4 seasons characterized by different meteorological conditions. For considered stations atmospheric pollutants and meteorological variables for different seasons positive and negative associations have been found and explained.
AB - The paper studies trend associations between atmospheric pollutants and meteorological variables time series of Mexico City Metropolitan Area (MCMA) by applying the Moving Approximation Transform (MAP). This recently introduced technique measures and visualizes associations of the dynamics between different time series in the form of an association network. The paper studies associations between 5 atmospheric pollutants (SO2, O3, NO2, NOx and PM2.5) and 7 meteorological variables (mean wind velocity, minimum, average and maximum values of both temperature and relative humidity) measured daily during one year in three meteorological stations located in different zones of MCMA. These associations were studied for 4 seasons characterized by different meteorological conditions. For considered stations atmospheric pollutants and meteorological variables for different seasons positive and negative associations have been found and explained.
KW - MAP transform
KW - Time series data mining
KW - atmospheric pollutants
KW - trend associations
UR - http://www.scopus.com/inward/record.url?scp=79960134418&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21587-2_11
DO - 10.1007/978-3-642-21587-2_11
M3 - Contribución a la conferencia
SN - 9783642215865
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 95
EP - 102
BT - Pattern Recognition - Third Mexican Conference, MCPR 2011, Proceedings
T2 - 3rd Mexican Conference on Pattern Recognition, MCPR 2011
Y2 - 29 June 2011 through 2 July 2011
ER -