战术导弹数据挖掘平台设计及其关键技术
|
摘要
为了优化导弹生产流程、降低武器装备寿命周期费用、利用导弹在生产和使用维护阶段获取的海量数据,运用数据挖掘技术,提出了导弹数据挖掘平台的总体设计思路;对导弹数据挖掘过程中的数据预处理方法、数据挖掘算法和异常检测算法等关键技术进行了研究,采用FP-Growth算法挖掘导弹生产过程中的工艺参数与产品质量的关联,采用Z-Score检测法完成异常参数检测;通过在导弹全寿命周期中的应用,方案合理可行,可以有效地提高导弹质量和装备的战备完好性,具有广阔的军事应用前景。
In order to optimize the production process and reduce life cycle costs of the tactical missile,the general design thinking on the missile data mining platform is put forward using huge amounts of data in the production,use and maintenance phase.Data preprocessing methods,data mining algorithms and anomaly detection algorithms are studied in the process of the missile data mining.FP-Growth algorithm is adopted to mine the association with the process parameters and products quality.Z-Score detection method is adopted to detect anomaly parameters.Practical application shows that these methods can enhance missile quality and operational readiness.It has a wide foreground of military application.
In order to optimize the production process and reduce life cycle costs of the tactical missile,the general design thinking on the missile data mining platform is put forward using huge amounts of data in the production,use and maintenance phase.Data preprocessing methods,data mining algorithms and anomaly detection algorithms are studied in the process of the missile data mining.FP-Growth algorithm is adopted to mine the association with the process parameters and products quality.Z-Score detection method is adopted to detect anomaly parameters.Practical application shows that these methods can enhance missile quality and operational readiness.It has a wide foreground of military application.
引文
[1]White House Office of Science and Technology Policy.Big Data is a Big Deal[EB/OL].[2012-03-29].http:∥www.whitehouse.gov/blog/2012/03/29/big data big deal.
[2]White House Executive Office of the President.Big Data across the Federal Government[EB/OL].[2012-03-29].http:∥www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_fact_sheet.pdf.
[3]Wang Weihang.The British Provides Huge Sum of Money for Developing Big Data Technologies to Promote Economic Growth[EB/OL].[2013-05-31].http:∥www.e-gov.org.cn/xinxihua/news003/201305/141545.html.
[4]Tan Pangning,Michal Steinbach,Vipin Kumar.数据挖掘导论[M].北京:人民邮电出版社,2011:2-3.
[5]FIU-Miner[EB/OL].http://www.Datamining-node08.cs.fiu.edu/FIU-Miner/.
[6]李秀娟,田川,冯欣.数据挖掘分类技术研究与分析[J].现代电子技术,2010,33(20):86-88.
[7]辛芳芳,焦李成,王桂婷.非局部均值加权的动态模糊.Fisher分类器的遥感图像变化检测[J].测绘学报,2012,41(4):584-590.
[8]李晖,肖鹏峰,冯学智,等.基于向量场模型的多光谱遥感图像多尺度边缘检测[J].测绘学报,2012,41(1):100-107.
[9]Han J,Pei J,Yin Y.Mining frequent patterns without candidate generation[R].In ACM SIGMOD Record,2000,29:1-12.
[10]李涛,等.数据挖掘的应用与实践[M].厦门:厦门大学出版社,2013.
[2]White House Executive Office of the President.Big Data across the Federal Government[EB/OL].[2012-03-29].http:∥www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_fact_sheet.pdf.
[3]Wang Weihang.The British Provides Huge Sum of Money for Developing Big Data Technologies to Promote Economic Growth[EB/OL].[2013-05-31].http:∥www.e-gov.org.cn/xinxihua/news003/201305/141545.html.
[4]Tan Pangning,Michal Steinbach,Vipin Kumar.数据挖掘导论[M].北京:人民邮电出版社,2011:2-3.
[5]FIU-Miner[EB/OL].http://www.Datamining-node08.cs.fiu.edu/FIU-Miner/.
[6]李秀娟,田川,冯欣.数据挖掘分类技术研究与分析[J].现代电子技术,2010,33(20):86-88.
[7]辛芳芳,焦李成,王桂婷.非局部均值加权的动态模糊.Fisher分类器的遥感图像变化检测[J].测绘学报,2012,41(4):584-590.
[8]李晖,肖鹏峰,冯学智,等.基于向量场模型的多光谱遥感图像多尺度边缘检测[J].测绘学报,2012,41(1):100-107.
[9]Han J,Pei J,Yin Y.Mining frequent patterns without candidate generation[R].In ACM SIGMOD Record,2000,29:1-12.
[10]李涛,等.数据挖掘的应用与实践[M].厦门:厦门大学出版社,2013.