Wavelets and Support Vector Machine for Forecasting the Meteorological Pollution

The paper presents the method of daily air pollution forecasting by using support vector machine (SVM) and wavelet decomposition. The considerations are presented for the NO₂, CO, SO₂ and dust concentrations. The prediction is made on the basis of the past pollution observation as well as the meteorological parameters, like wind, temperature, humidity and pressure. We propose the forecasting approach, applying the neural network of SVM type, working in the regression mode and wavelet decomposition of the measured time series data. The paper presents the results of numerical experiments on the basis of the measurements made by the meteorological stations, situated in the northern region of Poland