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Link16时隙选择算法分析   总被引:1,自引:0,他引:1  
无中心节点的组网方式是link16的一个关键技术。提出了一种自主预约时隙算法,可以有效地实现link16的动态网络管理,发挥link16更灵活的作用。针对此算法,分析了多个用户下的时隙冲突概率,并提出了一种简单有效的解决时隙冲突的方法。  相似文献   
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Many human-machine collaborative support scheduling systems are used to aid human decision making by providing several optimal scheduling algorithms that do not take operator’s attention into consideration. However, the current systems should take advantage of the operator’s attention to obtain the optimal solution. In this paper, we innovatively propose a human-machine collaborative support scheduling system of intelligence information from multi-UAVs based on eye-tracker. Firstly, the target recognition algorithm is applied to the images from the multiple unmanned aerial vehicles (multi-UAVs) to recognize the targets in the images. Then, the support system utilizes the eye tracker to gain the eye-gaze points which are intended to obtain the focused targets in the images. Finally, the heuristic scheduling algorithms take both the attributes of targets and the operator’s attention into consideration to obtain the sequence of the images. As the processing time of the images collected by the multi-UAVs is uncertain, however the upper bounds and lower bounds of the processing time are known before. So the processing time of the images is modeled by the interval processing time. The objective of the scheduling problem is to minimize mean weighted completion time. This paper proposes some new polynomial time heuristic scheduling algorithms which firstly schedule the images including the focused targets. We conduct the scheduling experiments under six different distributions. The results indicate that the proposed algorithm is not sensitive to the different distributions of the processing time and has a negligible computational time. The absolute error of the best performing heuristic solution is only about 1%. Then, we incorporate the best performing heuristic algorithm into the human-machine collaborative support systems to verify the performance of the system.  相似文献   
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