Operations command behavior knowledge representation learning method based on sequential graph

被引：0
|
作者：
Wang B. [1 ,2 ]
Wu L. [2 ]
Hu X. [2 ]
He X. [2 ]
Guo S. [2 ]
机构：
[1] Graduate School, National Defense University, Beijing
[2] Joint Operations College, National Defense University, Beijing
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2020年 / 42卷 / 11期
关键词：
Graph embedding; Joint operation; Knowledge representation learning; Operations command behavior; Sequential graph;
D O I：
10.3969/j.issn.1001-506X.2020.11.14
中图分类号：
学科分类号：
摘要：
In order to explore the modeling method of the sequential operations command behaviors knowledge deeply and effectively obtain the temporal correlation features of operations command behaviors of the commanders, an operations command behaviors knowledge representation learning method is proposed based on the sequential graph of wargaming operational orders. The operations command behaviors are presented by knowledge representation learning, and the model is verified by the task of operations command behaviors prediction. Experimental results show that the evaluating index is increased obviously, and the spatial-temporal features of operations command behaviors by the joint operations commanders are obtained effectively. Our work highlights the sequential joint operations command behavior representation learning and provides a foundation for the command experience extraction of joint operations commanders and joint operations situation cognition. © 2020, Editorial Office of Systems Engineering and Electronics. All right reserved.
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页码：2520 / 2528
页数：8
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