Prediction of carbon monoxide concentration near roads by means of artificial neural networks
نویسندگان
چکیده
The artificial neural petworks (ANN) as a tool /o predict air pollution were presented taking into account meteorological conditions and parameters which characterise the source of pollutants. A comparison was rpade between the two methods for calculation of carbon monoxide concentration in the region of a city road, The first method was based on a hybrid model which was a combination of ANN (a neural model based on radial basis iimctions – RBF) and the Pasquille model. In the other method the multilayer perception – MLP only, was applied to predict the level of carbon monoxide near the roadside edge. Topologies and the flow diagrams of signals in both networks were given and statistical estimation of the two methods was presented.
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