Information Group Discovery Technology of Battlefield Information Network Based on Deep Neural Networks
The battlefield information network is a complex network of personnel,equipment,weapon platforms and so on,and the discovery and determination of the battlefield information network information group can further locate the enemy's battlefield deployment and command relationship and provide more detailed intelligence support for operational decision-making.In the past research,most of the battlefield information network analysis focuses on the discovery of topology,this paper explores the use of node attribute information for information group discovery,first builds a virtual battlefield information network,simulates the battlefield intelligence group,accusation group and other information group communication,and construct node data set by capturing different information group node data packets to extract data features.Then,a DNN model is built to judge the information group attributes of nodes by using data characteristics as input.Finally,a virtual battlefield information network is built,and the trained DNN model is used to determine the information group to which the node belongs.
information groupdata characteristicsDeep Learning
国家科技期刊平台
NSTL
万方数据
