A Data Analysis Algorithm of Missing Point Association Rules for Air Target

摘要：

　　It is important to analyze missing point phenomenon in early warning.By using data mining method,the association rules between air target missing point and status of early warning equipment can be concluded.A new mining algorithm is proposed,which firstly divided the target track into two categories,and then acquired the target air track net units with the same characters by clustering.Through matrix calculating and filtering false correlation sets,the association rules can be found.Experimental results demonstrated that this algorithm is efficient and accurate to mine the association rules among missing point events.

关键词： early warning data analysis data mining confidence

作者: Jiang Surong Lan Jiangqiao Yang Yuhai

作者单位: Fourth department Air Force Early Warning Academy Wuhan,China

会议类型: 国际会议

会议名称: The 14th International Symposium on Distributed Computing and Applications to Business,Engineering and Science(DCABES 2015)(第十四届分布式计算及其应用国际学术研讨会)

会议地点: 贵阳

会议语种:英文

页码: 300-303

在线出版日期: 2015-08-18（万方平台首次上网日期，不代表论文的发表时间）