M.G. Cortina, U.S. Mendoza, J.M. Barrón-Adame, D.Andina, A. Vega-Corona
A comparison between a linear regression model and a Non-linear regression model is presented in this work for
forecasting of pollution levels due to SO2 in Salamanca city, Gto. Prediction is performed by means of an Adaptive
Linear Neural Network (ADALINE) and a Generalized Regression Neural Network (GRNN). Prediction experiments
are realized for 1, 12 and 24 hours in advance, and the results for linear regression have been satisfactory. The
performance estimation of both models are determined using the Root Mean Squared Error (RMSE) and Mean
Absolute Error (MAE). Obtained results are compared. The final results indicated that ADALINE outperforms the
past approach using GRNN.
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Interesting paper to read. You used the ADA ANN algorithm for perdicting So2 polution, does it also imply that other air polutions can also be perdicted by using ADA ANN network to obtain better result than GRNN?