指挥控制知识自动化关键技术研究
发布时间：2018-12-07 10:28
【摘要】：21世纪的战争形态表现为网络化体系条件下的一体化联合作战,为了实现军队成为一个互连互通的网络化实体,创造战场的信息优势,进而形成作战优势,从而实现完全意义上的协同作战,指挥控制知识自动化是必须解决的关键问题。在指挥控制知识自动化研究领域中需要解决的技术问题非常多,本文主要针对指挥控制知识自动化研究领域中的联合信息环境下,对各类分布式海量异构战场信息的共享、交换和存储技术开展研究工作。首先,针对联合战场信息多源异构复杂,并且现有的各种指挥控制信息系统普遍存在着信息“烟囱”问题,不能很好的满足网络化体系下的联合作战需求。借鉴语义网理论和知识工程方法,本文提出了基于语义网的面向分布式海量异构战场信息共享、交换和存储的总体框架方案,为指挥控制知识自动化提供基础理论支撑。第二,当所有战场信息都整合成为资源描述框架(RDF,Resources Description Framework)数据实现共享之后,为了使以关系数据库为基础的现有指挥控制系统能够访问RDF形式的共享信息,我们综合应用Jena框架、本体向关系数据库映射等技术,提出并实现了一种RDF数据向关系数据库的转换方法,从而达到在各个军兵种现有指挥控制系统基本不变的基础上实现信息共享目的。第三,随着联合战场信息的指数式增长,传统关系数据库无法满足海量RDF的高效存储和查询,战场信息RDF数据的分布式管理是未来大数据作战的必然趋势。针对这一现状,我们重点研究并提出一种基于Hadoop的海量战场信息一致性RDF存储和查询方法。通过构建基于Hadoop的分布式文件系统(HDFS,Hadoop Distributed File System),利用HDFS的非关系数据库HBase来实现海量军事RDF的存储和查询;另外,为了提高海量战场信息RDF数据的存储效率,还提出了一种通过分布式计算MapReduce进行数据解析的方法,从而实现海量军事RDF数据的高效存储、实时查询和挖掘,为作战决策提供强有力的保障。第四,基于Eclipse集成开发环境,设计与实现了一个海量战场信息RDF数据存储和查询的原型软件平台,该软件平台集成了RDF数据到关系数据库的转换、海量战场信息RDF数据的存储和查询、计算机集群状态管理等功能,验证了本文技术方案的可行性,为联合作战提供有力支持。
[Abstract]:The form of war in the 21st century is an integrated joint operation under the condition of networked system. In order to make the army become an interconnected networked entity, and create the information superiority of the battlefield, and then form the combat advantage, Therefore, the automation of command and control knowledge is the key problem to be solved. There are many technical problems to be solved in the field of command and control knowledge automation. This paper aims at sharing all kinds of distributed and heterogeneous battlefield information under the joint information environment in the field of command and control knowledge automation. Research on exchange and storage technology. First of all, because of the complexity of multi-source and heterogeneity of joint battlefield information, and the existing command and control information systems generally exist information "chimney" problem, it can not meet the needs of joint operations under the network system. Based on the semantic web theory and knowledge engineering method, this paper proposes a general framework for distributed heterogeneous battlefield information sharing, exchange and storage based on semantic web, which provides the basic theoretical support for the automation of command and control knowledge. Second, when all battlefield information is integrated into a resource description framework (RDF,Resources Description Framework) data sharing), in order to enable existing command and control systems based on relational databases to access shared information in the form of RDF, Based on Jena framework and ontology to relational database mapping technology, we propose and implement a method to convert RDF data to relational database. In order to achieve the goal of information sharing on the basis of the existing command and control system of all arms and arms. Third, with the exponential growth of joint battlefield information, the traditional relational database can not satisfy the efficient storage and query of massive RDF. The distributed management of battlefield information RDF data is the inevitable trend of big data in the future. In view of this situation, we focus on research and propose a massive battlefield information consistent RDF storage and query method based on Hadoop. A distributed file system based on Hadoop is constructed (HDFS,Hadoop Distributed File System), uses HDFS's non-relational database HBase to realize the storage and query of massive military RDF; In addition, in order to improve the storage efficiency of massive battlefield information RDF data, a method of data analysis through distributed computing MapReduce is proposed to realize the efficient storage, real-time query and mining of massive military RDF data. To provide a strong guarantee for operational decisions. Fourthly, based on the Eclipse integrated development environment, a prototype software platform for storing and querying massive battlefield information RDF data is designed and implemented. The software platform integrates the conversion of RDF data to relational database. The storage and query of massive battlefield information RDF data, computer cluster state management and other functions verify the feasibility of this technical scheme, and provide a strong support for joint operations.
【学位授予单位】：杭州电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：E86;TP311.13
本文编号：2367060
[Abstract]:The form of war in the 21st century is an integrated joint operation under the condition of networked system. In order to make the army become an interconnected networked entity, and create the information superiority of the battlefield, and then form the combat advantage, Therefore, the automation of command and control knowledge is the key problem to be solved. There are many technical problems to be solved in the field of command and control knowledge automation. This paper aims at sharing all kinds of distributed and heterogeneous battlefield information under the joint information environment in the field of command and control knowledge automation. Research on exchange and storage technology. First of all, because of the complexity of multi-source and heterogeneity of joint battlefield information, and the existing command and control information systems generally exist information "chimney" problem, it can not meet the needs of joint operations under the network system. Based on the semantic web theory and knowledge engineering method, this paper proposes a general framework for distributed heterogeneous battlefield information sharing, exchange and storage based on semantic web, which provides the basic theoretical support for the automation of command and control knowledge. Second, when all battlefield information is integrated into a resource description framework (RDF,Resources Description Framework) data sharing), in order to enable existing command and control systems based on relational databases to access shared information in the form of RDF, Based on Jena framework and ontology to relational database mapping technology, we propose and implement a method to convert RDF data to relational database. In order to achieve the goal of information sharing on the basis of the existing command and control system of all arms and arms. Third, with the exponential growth of joint battlefield information, the traditional relational database can not satisfy the efficient storage and query of massive RDF. The distributed management of battlefield information RDF data is the inevitable trend of big data in the future. In view of this situation, we focus on research and propose a massive battlefield information consistent RDF storage and query method based on Hadoop. A distributed file system based on Hadoop is constructed (HDFS,Hadoop Distributed File System), uses HDFS's non-relational database HBase to realize the storage and query of massive military RDF; In addition, in order to improve the storage efficiency of massive battlefield information RDF data, a method of data analysis through distributed computing MapReduce is proposed to realize the efficient storage, real-time query and mining of massive military RDF data. To provide a strong guarantee for operational decisions. Fourthly, based on the Eclipse integrated development environment, a prototype software platform for storing and querying massive battlefield information RDF data is designed and implemented. The software platform integrates the conversion of RDF data to relational database. The storage and query of massive battlefield information RDF data, computer cluster state management and other functions verify the feasibility of this technical scheme, and provide a strong support for joint operations.
【学位授予单位】：杭州电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：E86;TP311.13
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