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.
This paper presents a fast and new deterministic model selection methodology for incremental radial basis function neural network (RBFNN) construction in time series prediction problems. The development of such special designed methodology is motivated by the problems that arise when using a K-fold cross-validation-based model selection methodology for this paradigm: its random nature and the subjective...
Radial basis function neural networks (RBFNNs) are well known because, among other applications, they present a good performance when approximating functions although their design still remains as a difficult task. The function approximation problem arises in the construction of a control system to optimize the process of the mineral reduction. In order to regulate the temperature of the ovens and...
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.