Air Pollutant Level Estimation Applying a Self-organizing Neural Network

摘要: This paper presents a novel Neural Network application in order to estimate Air Pollutant Levels. The considers both concentrations and Meteorological variables. In compute the Level method three important stages. first stage, A process validate data information built threedimensional Information Feature Vector with wind speed direction meteorological variables is developed. orderly like time series Level. second considering behavior space knowledge priori about pollutant distribution Representative reduces computational cost training process. last designed trained Threedimensional Vector, then using estimated. real from an Automatic Environmental Monitoring Salamanca, Guanajuato, Mexico, therefore this proposal also