结合动态时间弯曲与决策树方法的液体火箭发动机故障诊断

对某大型液体火箭发动机的热试车数据及通过发动机模型仿真得到的故障数据进行动态时间弯曲分析,得到弯曲路径集,然后结合决策树方法进行了故障检测和诊断。对于故障试车没有出现漏报警和误报警,对于正常试车没有出现误报警。通过与神经网络、支持向量机等方法所得结果的对比,证明该方法可以成功地应用于火箭发动机的故障检测和诊断。     

航空兵编队空战决策模型研究

针对航空兵编队空战决策问题,从单机和编队两个层次上建立了编队威胁评估模型;并在此基础上建立了编队目标分配、攻击排序及火力分配模型;以5对8编队空战为例进行了仿真计算,计算结果表明,该模型能较好的解决多机种编队空战的战术决策问题。     

基于RS理论的电子对抗装备编配辅助决策方法

根据电子对抗装备编配的主要特点,提出利用RS(RoughSet)理论探索装备编配问题。综合考虑影响装备编配的各种因素,建立起知识表达系统,并且约简得到一些相对简单的编配规则;然后再根据实际情况,结合数学规划方法进行装备编配优化。分析结果表明,运用RS理论,能够较好地用定性与定量的方法解决电子对抗装备编配问题。     

车载光学测量设备任务调度问题建模与求解

为提高观测方案效费比、改进探测能力,探索了一类车载光学测量设备的观测任务调度问题,并给出了解决方案.将观测任务调度问题建模为一个寻找最优观测方案的数学问题,结合设备的性能特点,给出了观测方案的数学描述,梳理了观测方案应满足的约束,提出了评价观测方案质量的指标,进而利用多属性决策方法来计算不同方案的总体效能,并排序获得最...     

基于组合熵权的联合作战目标选择模型研究

针对作战中目标选择与排序问题,分析确定了8种在联合作战条件下影响目标选择关键因素。在此基础上应用多属性决策理论,以组合熵权系数确定指标权重,建立了目标选择模型。模型简洁易于实现,并且在决策中有效减少了主观随意性。最后通过仿真实例说明了模型的有效性和可操作性。     

A sequential partial information bomber-defender shooting problem

A bomber carrying homogenous weapons sequentially engages ground targets capable of retaliation. Upon reaching a target, the bomber may fire a weapon at it. If the target survives the direct fire, it can either return fire or choose to hold fire (play dead). If the former occurs, the bomber is immediately made aware that the target is alive. If no return fire is seen, the true status of the target is unknown to the bomber. After the current engagement, the bomber, if still alive, can either re-engage the same target or move on to the next target in the sequence. The bomber seeks to maximize the expected cumulative damage it can inflict on the targets. We solve the perfect and partial information problems, where a target always fires back and sometimes fires back respectively using stochastic dynamic programming. The perfect information scenario yields an appealing threshold based bombing policy. Indeed, the marginal future reward is the threshold at which the control policy switches and furthermore, the threshold is monotonic decreasing with the number of weapons left with the bomber and monotonic nondecreasing with the number of targets left in the mission. For the partial information scenario, we show via a counterexample that the marginal future reward is not the threshold at which the control switches. In light of the negative result, we provide an appealing threshold based heuristic instead. Finally, we address the partial information game, where the target can choose to fire back and establish the Nash equilibrium strategies for a representative two target scenario.     

地空导弹C3I决策系统的Petri网建模与性能分析

对地空导弹决策系统的结构和性能进行了研究.对基于旅营两级决策组织导出的库所/变迁系统进行了描述,建立了较为完善的决策系统的Petri网模型.并引入了决策时延这一反应指挥决策系统能力的重要性指标.这些问题的解决对提高C3I决策系统的实时性和准确性具有十分重要的意义.     

基于数学形态学的三维空间聚类

分析了各种空间聚类的方法,研究了炮阵地地形分析和选取原则,实现了炮阵地选取决策支持系统,提出了基于数学形态学的三维空间聚类新算法,并将该算法运用到开发的炮阵地选取决策支持系统中,实验结果表明,该算法效果较好.     

美国海军水面舰艇导弹防空体系分析

分析了美国海军防空作战思想,在此前提下总结出美海军舰空导弹体系主要的作战任务,说明了美海军典型水面舰艇装备舰空导弹的情况,最后阐述了今后美舰空导弹的发展趋势。     

Dynamic policy for idling time preservation

This study aims to determine and evaluate dynamic idling policies where an agent can idle while some customers remain waiting. This type of policies can be employed in situations where the flow of urgent customers does not allow the agent to spend sufficient time on back-office tasks. We model the system as a single-agent exponential queue with abandonment. The objective is to minimize the system's congestion while ensuring a certain proportion of idling time for the agent. Using a Markov decision process approach, we prove that the optimal policy is a threshold policy according to which the agent should idle above (below) a certain threshold on the queue length if the congestion-related performance measure is concave (convex) with respect to the number of customers present. We subsequently obtain the stationary probabilities, performance measures, and idling time duration, expressed using complex integrals. We show how these integrals can be numerically computed and provide simpler expressions for fast-agent and heavy-traffic asymptotic cases. In practice, the most common way to regulate congestion is to control access to the service by rejecting some customers upon arrival. Our analysis reveals that idling policies allow high levels of idling probability that such rejection policies cannot reach. Furthermore, the greatest benefit of implementing an optimal idling policy occurs when the objective occupation rate is close to 50% in highly congested situations.