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.
To effectively reduce the occurrence rate of axle faults of electric multiple units (EMUs), in this study, classical Apriori algorithm is improved based on Apache Hadoop big data and applied to prediction studies of axle faults of EMUs. First, for deficiencies of the classical Apriori algorithm, the improved Apriori algorithm that is constrained by business experience is proposed under the MapReduce...
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.