基于功能树的导弹打击系统目标瞄准点选择方法

针对导弹打击系统目标的问题,建立了基于目标功能损伤度的瞄准点选择方法;在对毁伤树方法进行改进的基础上,提出了描述目标结构与工作流程的目标功能树模型,构造出体现目标整体功能下降的优化目标函数,采用模拟退火算法搜索最优解。通过算例对不同的瞄准点选择方案进行比较,发现考虑目标的功能结构特点时,得到的瞄准点明显优于其它方案。     

光电坐标传感器在光幕靶中的应用

针对光电报靶系统的标校问题,以及可见光光幕靶光电接收器检测灵敏度的一致性和与海量数据的高速采集问题,采用大发射角的LED发光管,设计了光电开关电路和高速采样保持电路,实现了基于光电开关和取样电阻网络的光电坐标传感器,提高了系统的检测灵敏度和一致性,降低了系统设计的难度和成本。试验证明：该方法精度较高,具有良好的应用前景。     

无线传感器网络在环境监测中的应用

低成本、低功耗、自组网的无线传感器网络近年来得到快速发展.对近年来无线传感器网络在环境监测中的应用进展进行系统综述,对国内外各研究小组的研究成果进行对比和分析,最后对无线传感器网络的发展进行总结和展望.     

基于CAN总线的火灾监控系统研究与应用

论述了以CAN总线为基础的火灾监控系统的设计与实现方案,包括系统总体方案、系统硬件与软件设计,并结合实际工程对系统进行了实验研究。该监控系统可以方便地集成多种传感器和联动设备,在信息传输的安全性、准确性、实时性方面达到了较高要求,并且可以很方便地在此硬件平台的基础上实现分布式的智能火灾探测与控制,能满足大部分的监控需要,具有良好的应用前景。     

导弹贮存寿命预估的组合模型

在分析比较了几种寿命预估方法优缺点的基础上,针对单一预估方法在解决实际问题中所暴露的局限性,优选了GM-BPNN组合预估模型。该组合模型既利用了灰色预估理论具有所需要的样本数据少、原理简单、运算方便、短期预估精度高、可检验等优点,也发挥了神经网络并行计算、容错能力强、自适应能力强等优点。最后利用该组合模型对弹上某设备寿命进行了预估,取得了较好的预测效果。     

概率分布模型的飞机战备完好率评估与预测

飞机战备完好率是军用飞机战斗力的重要体现.在分析目前部队常用的飞机战备完好率算法缺陷的基础上,建立了基于概率分布的飞机战备完好率计算模型,该模型体现了飞机任务可靠性、维修性与战备完好性之间的关系.以某型飞机为例,通过分析飞机任务可靠度,利用飞机可靠性、维修性、保障性及作战训练任务的历史统计数据,依据概率分布模型对飞机的...     

基于物元模型-AHP的联合电子防空作战效能评估

针对现代防空作战训练中联合电子防空作战效能评估的问题,引入物元模型,并结合层次分析法(AHP)提出了基于物元模型-AHP的联合电子防空作战效能评估方法.以某次复杂电磁环境下联合电子防空演习任务为背景,建立了作战效能评估指标体系和评估模型,给出了评估模型的仿真算例,结果表明,该方法在联合电子防空作战的效能评估中是可行和有...     

地空反辐射导弹武器系统作战效能影响评估模型

地空反辐射导弹武器系统融入战术防空体系对防空作战效能的影响如何定量评估是作战运用研究的重要问题。采用阶段概率分析法建立了打击空袭方预警机、电子干扰机对防空作战效能和我方航空兵突击作战效能影响评估模型,通过计算可得出定量数据供作战研究参考。实例计算结果表明地空反辐射导弹武器系统将能极大地提高防空导弹体系作战效能,对于获取防对抗中的信息优势将发挥举足轻重的作用,对地面防空由被动防御向攻防兼备转型将其有重大意义。     

Using stochastic programming to solve an outpatient appointment scheduling problem with random service and arrival times

We study a stochastic outpatient appointment scheduling problem (SOASP) in which we need to design a schedule and an adaptive rescheduling (i.e., resequencing or declining) policy for a set of patients. Each patient has a known type and associated probability distributions of random service duration and random arrival time. Finding a provably optimal solution to this problem requires solving a multistage stochastic mixed‐integer program (MSMIP) with a schedule optimization problem solved at each stage, determining the optimal rescheduling policy over the various random service durations and arrival times. In recognition that this MSMIP is intractable, we first consider a two‐stage model (TSM) that relaxes the nonanticipativity constraints of MSMIP and so yields a lower bound. Second, we derive a set of valid inequalities to strengthen and improve the solvability of the TSM formulation. Third, we obtain an upper bound for the MSMIP by solving the TSM under the feasible (and easily implementable) appointment order (AO) policy, which requires that patients are served in the order of their scheduled appointments, independent of their actual arrival times. Fourth, we propose a Monte Carlo approach to evaluate the relative gap between the MSMIP upper and lower bounds. Finally, in a series of numerical experiments, we show that these two bounds are very close in a wide range of SOASP instances, demonstrating the near‐optimality of the AO policy. We also identify parameter settings that result in a large gap in between these two bounds. Accordingly, we propose an alternative policy based on neighbor‐swapping. We demonstrate that this alternative policy leads to a much tighter upper bound and significantly shrinks the gap.     

Multi-objectives nonlinear structure optimization for actuator in trajectory correction fuze subject to high impact loadings

This paper presents an actuator used for the trajectory correction fuze, which is subject to high impact loadings during launch. A simulation method is carried out to obtain the peak-peak stress value of each component, from which the ball bearings are possible failures according to the results. Subsequently, three schemes against impact loadings, full-element deep groove ball bearing and integrated raceway, needle roller thrust bearing assembly, and gaskets are utilized for redesigning the actuator to effectively reduce the bearings' stress. However, multi-objectives optimization still needs to be conducted for the gaskets to decrease the stress value further to the yield stress. Four gasket's structure parameters and three bearings' peak-peak stress are served as the four optimization variables and three objectives, respectively. Optimized Latin hypercube design is used for generating sample points, and Kriging model selected according to estimation result can establish the relationship between the variables and objec-tives, representing the simulation which is time-consuming. Accordingly, two optimization algorithms work out the Pareto solutions, from which the best solutions are selected, and verified by the simulation to determine the gaskets optimized structure parameters. It can be concluded that the simulation and optimization method based on these components is effective and efficient.