%0 Journal Article
%T 军用信息系统智能化的挑战与趋势<br>Challenges and trends in intelligent military information system
%A 郭圣明
%A 贺筱媛
%A 胡晓峰
%A 吴琳
%A 欧微
%J 控制理论与应用
%D 2016
%R 10.7641/CTA.2016.60470
%X 军用信息系统作为体系能力的倍增器,最近几十年取得了突出的成就. 但也面临极大的挑战, 尤其是以理 解、推理、决策为代表的智能化认知技术成为当前信息系统智能化发展的瓶颈. 本文在剖析当前军用信息系统智能 化需求的基础上,深入分析了以“深绿”计划为代表的指挥信息系统智能化发展现状和不足, 而以“深度学习”为 代表的智能化认知技术发展为军用信息系统智能化建设带来了机遇和挑战;综合考虑体系作战的复杂性特点, 提 出需要重点突破的智能认知关键技术;最后,结合国防大学兵棋演习数据,采用深度学习等技术,初步实现了对作战 体系威胁评估和作战态势优劣的智能化判断,展示了以深度学习为代表的智能认知技术在军事信息系统智能化建 设中的潜在应用价值.<br>Themilitary information system, as the ampli?er of systemof systems (SoS) effectiveness, havemade dramat- ic achievements in recent decades. However, it still faced huge challenges. Especially, the intelligent cognitive technology to understand, reasoning and decision-making, has become the bottleneck of current military information systems. Based on the analysis of the current requirement for the future military information system, we analyzed current development status and disparity of the intelligent technologies in-depth compared to the requirements taking example of Deep Green Plan, which was proposed by Defense Advanced Research Projects Agency (DARPA) of USA. The great development of intelligent cognitive technology owing to “deep learning”recently brings opportunities and challenges to the intelli- gent construction of the military information system. Considering the complexity of SoS operations, we suggest the key technologies of intelligent cognition for the military information system which needs to break through at present. Final- ly, we introduced our works on evaluation of operation SoS and operational situation evaluation based on deep learning technologies, and illustrated their advantage and feasibility in methodology.
%K 军用信息系统 深度学习 多层神经网络 威胁评估 态势判断&lt
%K br&gt
%K military information system deep learning multilayer neural networks threat evaluation operational
%U http://jcta.alljournals.ac.cn/cta_cn/ch/reader/view_abstract.aspx?file_no=CCTA160470&flag=1