Prediction of air contaminant concentration based on an associative pattern classifier
DOI:
https://doi.org/10.17533/udea.redin.13652Keywords:
pattern classification, Gamma classifier, air pollution predictionAbstract
From a little more than 15 years to this day, several methods and techniques taken from the area of Pattern Recognition have been employed on the treatment of data concerning environmental protection. In particular, diverse research groups have applied genetic algorithms and artificial neural networks to the prediction of data related to atmospheric sciences and the environment. In this paper, the authors present the results of applying the Gamma classifier to the prediction of future values for air contaminants concentration, obtaining competitive results (RMSE of 0.556382 ppm for carbon monoxide).
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