The Eztraction of Welding Type for Body in White Based on Association Rules

摘要：

To extract the reusable process knowledge of body in white (BIW) from process data, the association rule is employed to capture typical welding type. An association rule model for typical welding type acquisition is established. The attributes related to welding type are classified and quantitative attributes are partitioned into several intervals. Apriori algorithm is applied to extract the frequent itemsets. The strong rules are generated according to the threshold of confidence. Finally, a computational example mining typical welding process is analyzed. The result indicates that the approach can capture typical welding type effectively.

作者: CHAO Yongsheng LIU Haijiang LI Yun LIU Na

作者单位: College of Mechanical Engineering, Tongji University, Shanghai, China College of Mechanical Engineering, Tongji University, Shanghai, China 201804 College of Mechanical Engineering, Tongji University,Shanghai, China 201804 College of Mechanical Engineering, Tongji University Shanghai, China 201804

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Grey System and Intelligent Services(2009 IEEE灰色系统与服务科学国际会议)

会议地点: 南京

会议语种:英文

页码: 247-251

在线出版日期: 2009-10-20（万方平台首次上网日期，不代表论文的发表时间）