With the rapid development of informatization,autonomy and intelligence,unmanned swarm formation intelligent operations will become the main combat mode of future wars.Typical unmanned swarm formations such as ground-...With the rapid development of informatization,autonomy and intelligence,unmanned swarm formation intelligent operations will become the main combat mode of future wars.Typical unmanned swarm formations such as ground-based directed energy weapon formations,space-based kinetic energy weapon formations,and sea-based carrier-based formations have become the trump card for winning future wars.In a complex confrontation environment,these sophisticated weapon formation systems can precisely strike mobile threat group targets,making them extreme deterrents in joint combat applications.Based on this,first,this paper provides a comprehensive summary of the outstanding advantages,strategic position and combat style of unmanned clusters in joint warfare to highlight their important position in future warfare.Second,a detailed analysis of the technological breakthroughs in four key areas,situational awareness,heterogeneous coordination,mixed combat,and intelligent assessment of typical unmanned aerial vehicle(UAV)swarms in joint warfare,is presented.An in-depth analysis of the UAV swarm communication networking operating mechanism during joint warfare is provided to lay the theoretical foundation for subsequent cooperative tracking and control.Then,an indepth analysis of the shut-in technology requirements of UAV clusters in joint warfare is provided to lay a theoretical foundation for subsequent cooperative tracking control.Finally,the technical requirements of UAV clusters in joint warfare are analysed in depth so the key technologies can form a closed-loop kill chain system and provide theoretical references for the study of intelligent command operations.展开更多
随着网络业务的快速发展和网络技术的快速演进,人们对网络运维的要求也随之提高。当下的网络运维存在技术门槛高、闭环效率低、运维一致性差等问题。AI运维机器人基于NLP(Natural Language Processing,自然语言处理)技术,为运维人员提...随着网络业务的快速发展和网络技术的快速演进,人们对网络运维的要求也随之提高。当下的网络运维存在技术门槛高、闭环效率低、运维一致性差等问题。AI运维机器人基于NLP(Natural Language Processing,自然语言处理)技术,为运维人员提供极简的“对话式”运维操作,智能识别运维意图和操作对象,高效自动化执行任务,有效降低了运维人员的技术门槛,替代烦琐人工操作,有效提升了运维效率,实现了网络运维的提质增效。展开更多
基金the Natural Science Basic Research Program of Shaanxi(2023-JC-QN-0075,2022JM-395).
文摘With the rapid development of informatization,autonomy and intelligence,unmanned swarm formation intelligent operations will become the main combat mode of future wars.Typical unmanned swarm formations such as ground-based directed energy weapon formations,space-based kinetic energy weapon formations,and sea-based carrier-based formations have become the trump card for winning future wars.In a complex confrontation environment,these sophisticated weapon formation systems can precisely strike mobile threat group targets,making them extreme deterrents in joint combat applications.Based on this,first,this paper provides a comprehensive summary of the outstanding advantages,strategic position and combat style of unmanned clusters in joint warfare to highlight their important position in future warfare.Second,a detailed analysis of the technological breakthroughs in four key areas,situational awareness,heterogeneous coordination,mixed combat,and intelligent assessment of typical unmanned aerial vehicle(UAV)swarms in joint warfare,is presented.An in-depth analysis of the UAV swarm communication networking operating mechanism during joint warfare is provided to lay the theoretical foundation for subsequent cooperative tracking and control.Then,an indepth analysis of the shut-in technology requirements of UAV clusters in joint warfare is provided to lay a theoretical foundation for subsequent cooperative tracking control.Finally,the technical requirements of UAV clusters in joint warfare are analysed in depth so the key technologies can form a closed-loop kill chain system and provide theoretical references for the study of intelligent command operations.
文摘随着网络业务的快速发展和网络技术的快速演进,人们对网络运维的要求也随之提高。当下的网络运维存在技术门槛高、闭环效率低、运维一致性差等问题。AI运维机器人基于NLP(Natural Language Processing,自然语言处理)技术,为运维人员提供极简的“对话式”运维操作,智能识别运维意图和操作对象,高效自动化执行任务,有效降低了运维人员的技术门槛,替代烦琐人工操作,有效提升了运维效率,实现了网络运维的提质增效。
基金教育部高等教育司2020年第二批产学合作协同育人项目“基于产学合作的大数据人才培养改革与实践”(编号:202002112009)江苏省高校哲学社会科学研究课题“基于多模态信息融合的网络舆情监测研究”(编号:2022SJYB0982)无锡学院2021年教学改革研究课题“计算机操作系统实验教程(基于Visual Studio 2019)”(编号:JGYB202107)。
