Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial institutions.One of these AI technologies is using efficient and secure multi-environment Un...Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial institutions.One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles(UVs)for anti-submarine attacks.This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy.The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach,and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity solution.The research’s noteworthy findings demonstrate UVs’logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical information.The results suggest that detecting the submarine early increases the likelihood of averting a collision.The dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access efficiency.Securing communication between Unmanned Aerial Vehicles(UAVs)improves the level of secrecy necessary for the task.The swarm navigation is based on a peer-to-peer system,which allows each UAV to access information from its peers.This,in turn,helps the UAVs to determine the best route to take and to avoid collisions with other UAVs.The dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.展开更多
基于Agent的建模仿真(Agent Based Modeling and Simulation,ABMS)方法被普遍认为是军事作战研究特别是网络中心战(Network Centric Warfare,NCW)环境下进行作战研究的重要方法。采用ABMS仿真方法进行了CEC(Cooperative Engagement Capa...基于Agent的建模仿真(Agent Based Modeling and Simulation,ABMS)方法被普遍认为是军事作战研究特别是网络中心战(Network Centric Warfare,NCW)环境下进行作战研究的重要方法。采用ABMS仿真方法进行了CEC(Cooperative Engagement Capability)体系效能仿真分析。在体系效能分析仿真平台的支持下建立了面向CEC体系效能分析的Agent模型框架,确定了Agent实体间的探测、通信和毁伤交互关系。以舰艇编队数量和进攻强度和平台中心战(Platform CentricWarfare,PCW)、NCW和CEC指挥体制作为实验设计参数进行了批量仿真实验。通过与传统CEC体系效能分析结果的对比,发现了与传统的CEC体系效能分析研究存在的差异和原因,揭示了CEC对舰艇编队防空效能的贡献主要源于体系层次的行为控制。展开更多
基金This work was funded by the research center of the Future University in Egypt,in 2023.
文摘Utilizing artificial intelligence(AI)to protect smart coastal cities has become a novel vision for scientific and industrial institutions.One of these AI technologies is using efficient and secure multi-environment Unmanned Vehicles(UVs)for anti-submarine attacks.This study’s contribution is the early detection of a submarine assault employing hybrid environment UVs that are controlled using swarm optimization and secure the information in between UVs using a decentralized cybersecurity strategy.The Dragonfly Algorithm is used for the orientation and clustering of the UVs in the optimization approach,and the Re-fragmentation strategy is used in the Network layer of the TCP/IP protocol as a cybersecurity solution.The research’s noteworthy findings demonstrate UVs’logistical capability to promptly detect the target and address the problem while securely keeping the drone’s geographical information.The results suggest that detecting the submarine early increases the likelihood of averting a collision.The dragonfly strategy of sensing the position of the submersible and aggregating around it demonstrates the reliability of swarm intelligence in increasing access efficiency.Securing communication between Unmanned Aerial Vehicles(UAVs)improves the level of secrecy necessary for the task.The swarm navigation is based on a peer-to-peer system,which allows each UAV to access information from its peers.This,in turn,helps the UAVs to determine the best route to take and to avoid collisions with other UAVs.The dragonfly strategy also increases the speed of the mission by minimizing the time spent finding the target.
文摘基于Agent的建模仿真(Agent Based Modeling and Simulation,ABMS)方法被普遍认为是军事作战研究特别是网络中心战(Network Centric Warfare,NCW)环境下进行作战研究的重要方法。采用ABMS仿真方法进行了CEC(Cooperative Engagement Capability)体系效能仿真分析。在体系效能分析仿真平台的支持下建立了面向CEC体系效能分析的Agent模型框架,确定了Agent实体间的探测、通信和毁伤交互关系。以舰艇编队数量和进攻强度和平台中心战(Platform CentricWarfare,PCW)、NCW和CEC指挥体制作为实验设计参数进行了批量仿真实验。通过与传统CEC体系效能分析结果的对比,发现了与传统的CEC体系效能分析研究存在的差异和原因,揭示了CEC对舰艇编队防空效能的贡献主要源于体系层次的行为控制。
