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.
Support vector regression machine (SVR) has become a promising tool in many research fields, such as web intelligence, machinery fault diagnostic technique, dynamics environmental forecasting, and earthquake prediction, etc. Kernel method is most important to get more robust and higher generalization ability of SVR. In this paper, a new kernel, named Unified Chebyshev polynomial kernel (UCK), is proposed...
In the solution path algorithm of support vector regression, the penalty for violation of the required error is considered equally for every training sample, which means every training sample affects the generalization ability equally. Considering the existing of abnormal samples among the training data, for example noises with different variances, the weighted solution path algorithm of support vector...
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.