Abstract: Community structure mining in complex networks can help to grasp the principal tendency and skeleton relations of complex system. Based on establishing a model of networked command and control, a method of multi-granularity community structure mining with the help of local information detection is proposed in taking consideration of the characters of complexity and dynamic, and its efficiency and feasibility are verified through experiments, which provide new ideas and methods to observe command and control in networked operations.

Key words: networked command and control, community structure mining, local information detection, multi-granularity

摘要： 对复杂网络的社团结构进行数据挖掘有助于宏观把握复杂系统的主体倾向和骨干联系。在构建网络化指挥控制模型的基础上，从复杂性和动态性特征出发，提出基于局部信息检测的多粒度社团挖掘方法。实验分析结果表明，该方法有效、可行，为多视角观察网络化作战条件下的指挥控制提供了新的研究思路和分析方法。

关键词: 网络化指挥控制, 社团结构挖掘, 局部信息检测, 多粒度

CLC Number: 

• TP391.9