中国科技核心期刊      中国指挥与控制学会会刊     军事装备类重点期刊
Engineering & Application

Investigation on Warfare Simulation and Deduction Technology Based on Real-time Situation

  • WU Zhang-hua ,
  • CAO Zhi-min ,
  • JIA Zhen
Expand
  • Jiangsu Automation Research Institute, Lianyungang 222061, China

Received date: 2017-11-08

  Revised date: 2017-11-20

  Online published: 2022-05-14

Copyright

, 2018, Copyright reserved © 2018. Office of Acta Agronomica Sinica All articles published represent the opinions of the authors, and do not reflect the official policy of the Chinese Medical Association or the Editorial Board, unless this is clearly specified.

Abstract

Due to complex and multivariate characters of the modern warfare, the commanders are required to improve their ability of making decisions quickly. Based on the research on warfare simulation and deduction system, the differences between real-time situation and off-line simulation deduction systems are analyzed. And the operation deduction method, the deduction system frame, and the situation capturing and processing technology are studied respectively. As for uncertain target types of the situation information, a new KNN (K-Nearest Neighbor) algorithm is proposed to match with unknown target models. The resulting product has been applied to one theatre command information system.

Cite this article

WU Zhang-hua , CAO Zhi-min , JIA Zhen . Investigation on Warfare Simulation and Deduction Technology Based on Real-time Situation[J]. Command Control and Simulation, 2018 , 40(1) : 93 -97 . DOI: 10.3969/j.issn.1673-3819.2018.01.018

References

[1] 周云. 面向实时作战决策支持的动态数据驱动仿真理论和方法研究[D]. 长沙:国防科技大学, 2010: 4.
[2] 程路尧. 作战方案推演系统的设计与实现[J]. 舰船电子工程, 2014,34(11):9-12.
[3] 周云, 黄教民, 黄柯棣. 深绿计划关键技术研究综述[J]. 系统仿真学报, 2013,25(7):1633-1638.
[4] 窦林涛, 初阳, 周玉芳, 等. 平行仿真技术在指控系统中的应用构想[J]. 指挥控制与仿真, 2017,39(1):62-69.
[5] 胡晓峰, 郭圣明, 贺筱媛. 指挥信息系统的智能化挑战——“深绿”计划及AlphaGo带来的启示与思考[J]. 指挥信息系统与技术, 2016,7(3):1-7.
[6] 李小花, 李洙: 基于数据挖掘的战场目标综合识别技术[J]. 指挥控制与仿真, 2016,38(3):16-23.
[7] 苏毅娟, 邓振云, 程德波, 等. 大数据下的快速 KN N分类算法[J]. 计算机应用研究, 2016,33(4):1003-1006.
[8] 张著英, 黄玉龙, 王翰虎. 一个高效的KNN分类算法[J]. 计算机科学, 2008,35(3):170-172.
Outlines

/