复杂战场数据样本空间构建方法研究
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- 英文论文题名：Method of Building Sample Space for Complex Battlefield Data
- 论文作者：陈姣 ; 章慧钰 ; 周献中 ; 鞠恒荣 ; 杨佩
- 英文论文作者：CHEN Jiao ; ZHANG Hui-yu ; ZHOU Xian-zhong ; JU Heng-rong ; YANG Pei ; Department of Control & System Engineering ; Nanjing University ; Research Center for Novel Technology of Intelligent Equipment at Nanjing University
- 年：2017
- 作者机构：南京大学控制与系统工程系;南京大学智能装备新技术研究中心;
- 论文关键词：态势认知 ; 要素 ; 形式化 ; 标签生成
- 英文论文关键词：Situation Awareness ; Elements ; Formal ; Label Generation
- 会议召开时间：2017-07-03
- 会议录名称：第五届中国指挥控制大会论文集
- 语种：中文
- 分类号：E91
- 学会代码：ZHKZ
- 会议名称：第五届中国指挥控制大会
- 会议地点：中国北京
- 主办单位：中国指挥与控制学会
- 学会名称：中国指挥与控制学会
- 页数：5
- 文件大小：521k
- 原文格式：D
- 会议级别：全国
摘要
随着一体化联合作战的全面普及,复杂战场数据"爆炸"式的增长。然而,在目前关于战场态势认知的研究中,鲜有针对复杂战场的数据样本空间构建方法。合理有效的样本空间构建方法是指挥决策人员快速、准确理解战场态势的前提条件。针对这一问题,本文将初步探讨复杂战场数据样本空间构建方法,以本体思想为指引,对战场中的态势要素进行了分类,并构建了相应的形式化模型。基于此,提出了一种战场数据样本标签自动推理机制。通过以上讨论,能够为复杂战场环境中的态势认知提供理论支撑。
With the popularization of integrated joint operations, complex battlefield data grows in an explosive way. However, at present, in the research of battlefield situation awareness, there are few methods to construct the data space of the complex battlefield. A reasonable and effective method to construct the sample space is the precondition for the decision maker to understand the battlefield situation quickly and accurately. In order to solve this problem, in this paper, we will discuss the method of constructing the sample of complex battlefield data. Guided by ontology, the situation elements in the battlefield are classified, and the corresponding formal model is constructed. Based on such construction, an automatic inference mechanism for the battlefield data sample labels is presented in this paper. Through the above discussion, it can provide theoretical support for the situation awareness in the complex battlefield environment.
With the popularization of integrated joint operations, complex battlefield data grows in an explosive way. However, at present, in the research of battlefield situation awareness, there are few methods to construct the data space of the complex battlefield. A reasonable and effective method to construct the sample space is the precondition for the decision maker to understand the battlefield situation quickly and accurately. In order to solve this problem, in this paper, we will discuss the method of constructing the sample of complex battlefield data. Guided by ontology, the situation elements in the battlefield are classified, and the corresponding formal model is constructed. Based on such construction, an automatic inference mechanism for the battlefield data sample labels is presented in this paper. Through the above discussion, it can provide theoretical support for the situation awareness in the complex battlefield environment.
引文
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[2]《孙子》注释小组.孙子兵法新注[M].北京:中华书局,1977.
[3]Spick M.The ace factor:air combat&the role of situational awareness[M].1988,11:208.
[4]Endsley M R,Jones W M.A model of inter-and intrateam situation awareness:implications for design,training and measurement[C].Proceedings of New Trends in Cooperative Activities:Understanding System Dynamics in Complex Environments.Santa Monica,CA:Human Factors and Ergonomics Society,2001.
[5]Golestan K,Soua R,Karray F,et al.Situation awareness within the context of connected cars:a comprehensive review and recent trends[J].Information Fusion,2016,29(C):68-83.
[6]Blasch E,Kadar I,Salerno J,et al.Issues and challenges in situation assessment(level 2 fusion)[J].Journal of Advances in Information Fusion,2006,1(2):22-139.
[7]Liggins M,Hall D,Llinas J.Handbook of multisensor data fusion:theory and practice(Second Edition)[J].Artech House Radar Library,2008,39(5):180-184.
[8]Kokara M M,Matheusb C J,Baclawskic K.Ontology-based situation awareness[J].Information Fusion,2009,10(1):83-98.
[9]Rahmes M,Wilder K,Fox K,et al.A game theory model for situation awareness and management[C].Proceedings of IEEE Consumer Communications and NETWORKING Conference.IEEE,2013:909-913.
[10]Chen G,Shen D,Kwan C,et al.Game theoretic approach to threat prediction and situation awareness[C].Proceedings of International Conference on Information Fusion.IEEE,2006:1-8.
[11]Brynielsson J,Arnborg S.An information fusion game component[J].Journal of Advances in Information Fusion,2006,1(2):108-121.
[12]Isermann R,Mannale R,Schmitt K.Collision-avoidance systems PRORETA:situation analysis and intervention control[J].Control Engineering Practice,2012,20(11):1236-1246.
[13]杨洁.SOA架构下基于语义的人件服务管理与调用研究[D].南京大学,2014.
[14]周宁,刘解放.基于OWL的网络管理领域本体构建方法[J].内江师范学院学报,2009,24(10):76-78.
[15]刘兵,杨晋辉,赵永朋,等.装备指挥仿真构件形式化描述方法研究[C].2010系统仿真技术及其应用学术会议论文集,2010.
[16]Hotho A,J?schke R,Schmitz C,et al.Information Retrieval in Folksonomies:Search and Ranking[J].Semantic Web Research&Applications,2011,4011:411-426.
[17]Symeonidis P,Nanopoulos A,Manolopoulos Y.A Unified Framework for Providing Recommendations in Social Tagging Systems Based on Ternary Semantic Analysis[J].Knowledge&Data Engineering IEEE Transactions on,2010,22(2):179-192.
[18]Harvey M,Baillie M,Ruthven I,et al.Tripartite hidden topic models for personalised tag suggestion[C].European Conference on Advances in Information Retrieval.Springer-Verlag,2010:432-443.
[19]Li C,Datta A,Sun A.Semantic tag recommendation using concept model.[C].Proceeding of the,International ACM SIGIR Conference on Research and Development in Information Retrieval,SIGIR 2011,Beijing,China,July.DBLP,2011:1159-1160.
[20]Sun K,Wang X,Sun C,et al.A language model approach for tag recommendation[J].Expert Systems with Applications,2011,38(3):1575-1582.
[21]Lipczak M,Milios E.Efficient Tag Recommendation for Real-Life Data[J].Acm Transactions on Intelligent Systems&Technology,2011,3(1):2.
[22]Sheng,Y,Zhou,X,Yang,J,et al.Performance evaluation of the novel DSS based on humanware service[C].IEEE International Conference on Networking,Sensing and Control,2013:907-912.
[23]朱咸军,杨洁,胡文婷,等.新型决策系统中的人件服务技术体系研究[J].科技管理研究,2015.