排序方式: 共有134条查询结果,搜索用时 15 毫秒
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介绍了智能无人集群作战的相关概念,为反映智能无人仿真实体的自主能力和适应能力,提出将学习过程显性化的观察-判断-决策-行动-学习(Observe, Orient, Decide, Act and Learning, OODA-L)模式,并进一步扩展为适用于集群协同的Co-OODA-L模式。在智能无人仿真实体的总体描述上,采用马尔可夫决策过程进行数学抽象处理,提出智能无人Agent的三域分层结构。为体现智能无人集群作战的自主协同、分布式等特点,提出了利用人工神经网络将可变数量的智能无人Agent融合为同构或异构集群进行协同作战建模的体系结构。 相似文献
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通过试验研究气液同轴直流式和气液同轴离心式喷嘴的雾化性能。研究表明:喷嘴出口扩张时可以改善喷嘴的雾化性能;气液同轴直流式和气液同轴离心式喷嘴都存在一个合适的缩进长度,在改善喷嘴雾化特性的同时对总流量影响较小;在相同条件下,气液同轴离心式喷嘴的喷雾性能要优于气液同轴直流式喷嘴的喷雾性能。 相似文献
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受社会型生物群体行为启发,群体智能得到日益广泛的关注,机器人集群作为群体智能的重要承载者得到了大量研发和广泛应用.机器人集群路径规划技术作为一项核心关键技术也得到快速发展.为此全面深入地调研了机器人集群路径规划的技术发展现状,创新性地归纳了适用于不同集群规模、可扩展性要求、通信需求以及算法要求的集群规划基础计算架构,包... 相似文献
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任务分配是多UCAV协同控制的核心和有效保证。分析了影响目标价值毁伤、UCAV损耗、任务消耗时间等三项关键战技指标的因素,综合考虑实战中多UCAV同时攻击同一目标和使用软杀伤武器这两种典型情况对UCAV执行任务的影响,建立了针对攻击任务的多UCAV协同任务分配模型,并应用粒子群算法求解。仿真结果验证了模型的合理性和算法的有效性。 相似文献
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《防务技术》2020,16(2):299-307
In this paper, the gauge points setting is introduced in the SPH simulation to analyze the debris cloud structure generated by the hypervelocity impact of disk projectile on thin plate. Compared with the experiments, more detailed information of the debris cloud structure can be classified from the numerical simulation. However, due to the solitary dispersion and overlap display of the particles in the SPH simulation, accurate comparison between numerical and experimental results is difficult to be performed. To track the velocity and spatial distribution of the particles in the debris cloud induced from disk and plate, gauge points are locally set in the single-layer profile in the SPH model. By analyzing the gauge points’ spatial coordinate and velocity, the location and velocity of characteristic points in the debris cloud are determined. The boundary of debris cloud is achieved, as well as the fragments distribution outside the main structure of debris cloud. 相似文献
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《防务技术》2020,16(5):1062-1072
Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. To reduce the number of generated sub-graphs, overlap ratio metric is utilized for this purpose. After encoding the final selected sub-graphs, binary classification is then applied to classify the emotion of the queried input facial image using six levels of classification. Binary cat swarm intelligence is applied within each level of classification to select proper sub-graphs that give the highest accuracy in that level. Different experiments have been conducted using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the final system accuracy was 90.00%. The results show significant accuracy improvements (about 2%) by the proposed system in comparison to current published works in SAVEE database. 相似文献
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为了增强复杂电磁环境中航空集群战术网络的抗干扰能力,提出把同时收发认知抗干扰电台应用于航空集群网络节点,且每个节点采用改进能量检测方法进行干扰感知。在此基础上,分别研究了存在单/多个干扰源时的网络节点干扰感知性能,推导出干扰感知的虚警概率和检测概率的闭式表达。仿真结果表明,通过调节改进能量检测器的参数p,可以提高航空集群机载战术网络的干扰感知能力。 相似文献
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