Red Neuronal Artificial aplicado para el pronóstico de eventos críticos de PM2.5 en el Valle de Aburra.
Artificial neural network applied for the forecast of critical PM2.5 events in the Aburra Valley
DOI:
https://doi.org/10.15446/dyna.v86n209.63228Palabras clave:
Contaminación atmosférica, Pronóstico de PM2.5, Red Neuronal Artificial, Datos Meteorológicos (es)The great human health implications of exposure to atmospheric pollution events can have repercussions on the quality of life, economy,
and the quality of city’s ecosystems. With the possibility of predicting a critical event, the option of taking adequate measures for mitigation
or even prevention of these impacts is enabled. In this paper, an Artificial Neural Networks (RNA) model was developed and tested to
predict the daily concentration of particulate matter less than 2.5 microns (PM2.5) in the Aburrá Valley (Colombia), with a day of
anticipation, based on information from three stations of the Metropolitan Area Air Quality Monitoring Network.
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