基于混合相似度的反导作战案例检索方法
|
摘要
针对反导作战预案属性种类繁多、元素复杂等特性,为了更好地将作战预案与作战问题进行匹配,分析了反导作战预案各属性的差异,设计了一种先局部后整体的相似度量策略,将反导作战预案属性划分为关键类属性、裕度值属性、确定性数值属性、区间性数值属性、模糊属性和文本类属性6类,并给出了相应的相似度量算法。基于最近邻策略,提出了一种基于混合相似度的反导作战案例检索方法,并对该方法进行了实例验证,结果表明:该方法能有效提高反导作战案例检索的速度和正确率,可为反导指挥控制系统的建设提供技术支持。
According to the characteristics of the antimissile operation plan,such as various kinds of attributes and complex elements,in order to better match the operation plan with the operational issues,based on the analysis of each antimissile operation preplan differences,a similarity measure strategy that computes the whole case similarity after the partial one is designed. The antimissile operation plan attribute is classified into six kinds such as key attribute,margin value attribute,deterministic numerical attribute,interval numerical attribute,fuzzy attribute and semantically attribute,and corresponding similarity measure methods are presented. Based on the nearest neighbor strategy,a new case retrieval method of antimissile operation based on hybrid similarity is designed,and it is verified by the case example. The result shows that the method can improve the speed and the accuracy of case retrieval,which provides technical support for the construction of antimissile command and control system.
According to the characteristics of the antimissile operation plan,such as various kinds of attributes and complex elements,in order to better match the operation plan with the operational issues,based on the analysis of each antimissile operation preplan differences,a similarity measure strategy that computes the whole case similarity after the partial one is designed. The antimissile operation plan attribute is classified into six kinds such as key attribute,margin value attribute,deterministic numerical attribute,interval numerical attribute,fuzzy attribute and semantically attribute,and corresponding similarity measure methods are presented. Based on the nearest neighbor strategy,a new case retrieval method of antimissile operation based on hybrid similarity is designed,and it is verified by the case example. The result shows that the method can improve the speed and the accuracy of case retrieval,which provides technical support for the construction of antimissile command and control system.
引文
[1]李龙跃,刘付显,梅颖颖.末段反TBM火力-目标匹配优化及APSO求解算法[J].系统工程与电子技术,2013,35(5):993-999.
[2]李龙跃,刘付显,赵麟锋.对多波次目标直接分配到弹的反导火力规划方法[J].系统工程与电子技术,2014,36(1):2206-2212.
[3]顾东晓,李兴国,梁昌勇,等.案例检索及权重优化方法研究及应用[J].系统工程学报,2009,24(6):764-768.
[4]范海雄,刘付显,夏璐.融合裕度和否决权的案例相似度量方法[J].计算机工程,2012,38(12):261-264.
[5]任凯,浦金云.基于案例属性特征区间相似度的改进算法研究[J].控制与决策,2010,25(2):307-320.
[6]Stefanescu D,Banjade R,Rus V.A Sentence Similarity Method Based on Chunking and Information Content[J].Lecture Notes in Computer Science,2014,8403(1):442-453.
[7]Batet M,Sánchez D,Valls A,et al.Semantic Similarity Estimation from Multiple Ontologies[J].Applied Intelligence,2013,38(1):29-44.
[8]范海雄,刘付显,邹志刚.反导作战预案形式化建模研究[J].现代防御技术,2013,41(1):1-8,41.
[9]Armstrong M J.Effective Attacks in the Salvo Combat Model:Salvo Sizes and Quantities of Targets[J].Naval Research Logistics(NRL),2007,54(1):66-77.
[10]Armstrong M J.The Salvo Combat Model with Area Fire[J].Naval Research Logistics(NRL),2013,60(8):652-660.
[11]李龙跃,刘付显,田振浩,等.双层反导协同模式分析与距离度量优选法[J].装甲兵工程学院学报,2016,30(4):57-61.
[12]Ontan~ón S,Plaza E.Similarity Measures over Refinement Graphs[J].Machine Learning,2012,87(1):57-92.
[2]李龙跃,刘付显,赵麟锋.对多波次目标直接分配到弹的反导火力规划方法[J].系统工程与电子技术,2014,36(1):2206-2212.
[3]顾东晓,李兴国,梁昌勇,等.案例检索及权重优化方法研究及应用[J].系统工程学报,2009,24(6):764-768.
[4]范海雄,刘付显,夏璐.融合裕度和否决权的案例相似度量方法[J].计算机工程,2012,38(12):261-264.
[5]任凯,浦金云.基于案例属性特征区间相似度的改进算法研究[J].控制与决策,2010,25(2):307-320.
[6]Stefanescu D,Banjade R,Rus V.A Sentence Similarity Method Based on Chunking and Information Content[J].Lecture Notes in Computer Science,2014,8403(1):442-453.
[7]Batet M,Sánchez D,Valls A,et al.Semantic Similarity Estimation from Multiple Ontologies[J].Applied Intelligence,2013,38(1):29-44.
[8]范海雄,刘付显,邹志刚.反导作战预案形式化建模研究[J].现代防御技术,2013,41(1):1-8,41.
[9]Armstrong M J.Effective Attacks in the Salvo Combat Model:Salvo Sizes and Quantities of Targets[J].Naval Research Logistics(NRL),2007,54(1):66-77.
[10]Armstrong M J.The Salvo Combat Model with Area Fire[J].Naval Research Logistics(NRL),2013,60(8):652-660.
[11]李龙跃,刘付显,田振浩,等.双层反导协同模式分析与距离度量优选法[J].装甲兵工程学院学报,2016,30(4):57-61.
[12]Ontan~ón S,Plaza E.Similarity Measures over Refinement Graphs[J].Machine Learning,2012,87(1):57-92.