基于试验数据Apriori关联规则挖掘的数据采集方案设计优化

Design and Optimization of Data Acquisition Scheme Based on Apriori Association Rule Mining of Test Date

针对红外经纬仪测量系统弹道测试试验,如何在稍纵即逝的发射窗口期内达到较高的测试精度和目标捕获率问题,提出一种基于Apriori关联规则挖掘和PDCA戴明环相结合的试验数据再利用方法,通过对已有历史试验数据的分析挖掘,提取影响试验数据录取的事件因子,并分析其作用机理,构建数据采集方案设计优化策略集,采用阶跃PDCA方法对数据采集方案进行循环优化,并验证结论的有效性。结果表明,动态因果关系集和方案优化策略集可为后续性能试验、作战试验数据采集方案设计和改进提供参考和依据,对于提升目标捕获率和数据采集精度有一定辅助作用,探索了关联规则挖掘方法在试验数据再利用中的应用。

Aiming at the problem of the ballistic test of the infrared theodolite measuring system,how to achieve higher test accuracy and target capture rate within the transient launch window period,a new method of test data reuse based on the combination of Apriori association rule mining and PDCA Deming circle is proposed.Through the analysis and mining of the existing historical test data,the event factors that affect the admission of the test data are extracted and the mechanism of action is analyzed,and the data acquisition scheme design optimization strategy set is constructed.The stepped PDCA method is used to make loop optimization of the data acquisition scheme and verify the validity of the conclusions.The results show that the dynamic causal relationship set and scheme optimization strategy set can provide reference and basis for the design and improvement of subsequent performance test and combat test data acquisition scheme.They have a certain auxiliary effect on improving the target capture rate and data acquisition precision.The application of association rule mining method in the reuse of test data is explored.