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科技导报
| 科技引领 2019, 37(12): 86-91
人工智能时代智能化海战模式
全屏
张海, 陈小龙, 张财生, 黄勇
作者信息
通讯作者:
陈小龙(通信作者),副教授,研究方向为雷达信号处理、海上目标探测等,电子信箱:cxlcxl1209@163.com
Future intelligent naval warfare pattern: Artificial intelligence+
Affiliations
出版时间: 2019-06-28
doi: 10.3981/j.issn.1000-7857.2019.12.015
文章导航
现代海战场环境复杂,探测对象和作战形式多样,多平台装备呈现网络化特点,对传统的海战模式提出了新的要求和挑战。以人工智能在未来海战中的应用为主线,阐述了智能作战的概念及内涵,分析了人工智能融入作战的基本样式,总结了未来智能化海战模式的特点和规律以及智能化海战面临的瓶颈和挑战,并提出了适应未来智能化海战的建议。
人工智能
/
智能海战
/
网络化协同
/
智能探测
The modern sea battlefield environment is complex and the detection objects and the combat forms are diverse. At the same time, the multi-platform equipment has network features, with new requirements and challenges, as compared with that in the traditional naval battle model. With the rapid development of the artificial intelligence technology, the intelligent warfare is beginning to emerge. This paper introduces the concept and the connotation of the intelligent warfare with the application of the artificial intelligence in future naval battles, and analyzes the basic style of the artificial intelligence being integrated into the combat. The future characteristics and laws of the intelligent naval warfare pattern are introduced and the bottlenecks and the challenges faced by the intelligent naval warfare are systematically summarized. Finally, some measures and suggestions for adapting to the future intelligent naval warfare are discussed.
artificial intelligence
/
intelligent naval battle
/
networked collaboration
/
intelligent detection
张海, 陈小龙, 张财生, 黄勇.
人工智能时代智能化海战模式.
科技导报,
2019
, 37
(12)
: 86
-91
.
DOI: 10.3981/j.issn.1000-7857.2019.12.015
ZHANG Hai, CHEN Xiaolong, ZHANG Caisheng, HUANG Yong.
Future intelligent naval warfare pattern: Artificial intelligence+[J].
Science & Technology Review ,
2019
, 37
(12)
: 86
-91
.
DOI: 10.3981/j.issn.1000-7857.2019.12.015
2019年第37卷第12期
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文章信息
doi: 10.3981/j.issn.1000-7857.2019.12.015
接收时间:2019-05-20
首发时间:2019-06-24
出版时间:2019-06-28
收稿日期:2019-05-20
修回日期:2019-06-10
通讯作者:
陈小龙(通信作者),副教授,研究方向为雷达信号处理、海上目标探测等,电子信箱:cxlcxl1209@163.com
https://castjournals.cast.org.cn/joweb/kjdb/CN/10.3981/j.issn.1000-7857.2019.12.015
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2种不同金属材料的力学参数
科 Family 属数 Number of genus 种数 Number of species 占总种数比例 Percentage of total species (%) 属 Genus 种数 Number of species 占总种数比例 Percentage of total species (%) 鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78 小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39 多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39 红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87 小菇属 Mycena 11 5.26 光柄菇属 Pluteus 5 2.39 红菇属 Russula 17 8.13 栓菌属 Trametes 5 2.39
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