An Improved Apriori Algorithm for Early Warning of Equipment Failue

摘要：

With large database, the process of mining association rules is time consuming. The efficiency becomes crucial factor. By analyzing Apriori algorithm and its improvement, the improved Apriori algorithm is applied to early warning of equipment failure. Moreover, Apriori algorithm is improved by reducing the number of scanning data base and the number of candidate item-set in advance which might become frequent item. Apriori algorithm and the improved Apriori algorithm are compared by the example of equipment failure. Finally, the improved Apriori algorithm is proved that it can improve the efficiency by experiment.

关键词： association rules mining(ARM) Apriori algorithm early warning of equipment failure

作者: Liu Jing Lu Yongquan Wang Jintao Gao Pengdong Qiu Chu Ji Haipeng Li Nan Yu Wenhua

作者单位: High Performance Computing Center Department of Information Engineering Communication University of High Performance Computing Center Communication University of China BeiJing, China College of Mechanical Engineering YanShan University QinHangdao, China

会议类型: 国际会议

会议名称: 2009 2nd IEEE International Conference on Computer Science and Information Technology(第二届计算机科学与信息技术国际会议 ICCSIT2009)

会议地点: 北京

会议语种:英文

页码: 1771-1773

在线出版日期: 2009-08-08（万方平台首次上网日期，不代表论文的发表时间）