The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The paper presents the neural network approach to the accurate forecasting of the daily average concentration of PM10. Few neural predictors are applied: the multilayer perceptron, radial basis function, Elman network and support vector machine. They are used for prediction either in direct application or in combination with wavelet decomposition, forming many individual prediction results that will...
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,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.