高技术条件下炮兵作战火力优化模型

由于能给敌军造成大量的毁伤 ,炮兵被誉为“战争之神”。但是 ,由于可得到的炮兵部队数量、弹药和时间所限 ,炮兵不可能对战场所有可得到的目标射击。炮兵必须决定哪些目标可用炮兵射击 ,以及如何射击。考虑到未来战场将充斥着大量目标 ,炮兵要求使用一种自动目标处理系统。将提出一个炮兵优化模型 ,模型的目的是快速对目标价值排序 ,然后以最佳的炮兵兵力、火力分配对选择的目标进行射击。     

一体化联合作战指挥决策节点提前工作时间研究

分布式联合决策可缩短系统决策时间,提高决策质量.运用分布式联合决策,其关键点之一是确定各流程节点的工作开始时刻.依据影响分布式联合决策各节点开始工作时刻的主要因素是上下节点间传递的信息的特点,引入了信息熵的概念,通过一定的阈值来确立分布式联合决策系统中各节点的开始决策时刻.利用Bernstein多项式建立了分布式联合决策开始时刻数学模型,给出了求解该数学模型的方法,指出了该模型应用于实践的思路.     

多级电磁线圈发射器时序触发控制策略

为优化多级同步感应线圈电磁发射器性能,以提高发射速度和能量转换效率为检验指标,以影响上述指标的触发时序为优化对象,采用遗传算法建立单级同步感应线圈型电磁发射器触发位置优化数学模型,计算最佳触发位置,通过数值和有限元两种仿真系统对优化结果的正确性进行验证。采用该方法对两级以及十级同步感应线圈型电磁发射器的触发时序进行优化研究,并进行仿真验证。为解决仿真系统误差问题,提出采用动子线圈在各级的触发位置和速度作为控制因素的双控触发方式,并研究分析仿真过程中触发开关的随机抖动对出口速度误差的影响,得到最佳触发时序控制策略。     

An eikonal equation based path planning method using polygon decomposition and curve evolution

Path planning is a key technique of autonomous navigation for robots, and the velocity field is an important part. Constructing velocity field in a complex workspace is still challenging. In this paper, an inner normal guided segmentation algorithm in a complex polygon is proposed to decompose the complex workspace in this paper. The artificial potential field model based on probability theory is then used to calculate the potential field of the decomposed workspace, and the velocity field is obtained by utilizing the potential field of this workspace. Path optimization is implemented by curve evolution, during which the internal force generated in the smoothing process of the initial path by a mean filter and the external force is obtained from the gradient of the workspace potential field. The parameter selection principle is deduced by analyzing the influence of several parameters on the path length and smoothness. Simulation results show that the designed polygon decomposition algorithm can effectively segment complex workspace and that the path optimization algorithm can shorten and smoothen paths.     

拦截弹推进及弹道参数的模糊优化研究

在拦截弹推进系统和弹道参数的设计中 ,引入多目标多约束的模糊优化方法 ,在约束条件一定的情况下 ,合理选择和分配几个重要的设计变量 ,使得拦截弹的总质量最小、拦截时间最短。     

恒速航行原理的数学证明与分析

提出并证明了船舶经济航行的基本原理———恒速航行原理 .先将实际船舶航行中最经济航行的航速选择这个一般性问题抽象成纯数学问题 :在规定的时间内从A地航行到B地 ,如何选择航速以使推进系统总耗功最省 ;然后在数学上证明恒速航行原理 ,即恒速航行是船舶经济航行唯一的选择 ;最后 ,将该原理推广到其它交通手段 ,如车辆行驶和飞机飞行     

网络空间联合反恐作战信息共享能力分析与评估?

在网络空间联合反恐作战信息共享能力构成框架的基础上，分析了信息共享能力生成的相关要素及其内部关系，并利用信息熵理论建立了信息共享的时效熵、质量熵、成本熵模型。通过对传统树形链状和新型网状循环两种信息共享模式进行仿真分析，为不断提高信息共享能力进行了有益探索。     

Balancing a one‐way corridor capacity and safety‐oriented reliability: A stochastic optimization approach for metro train timetabling

In urban rail transit systems of large cities, the headway and following distance of successive trains have been compressed as much as possible to enhance the corridor capacity to satisfy extremely high passenger demand during peak hours. To prevent train collisions and ensure the safety of trains, a safe following distance of trains must be maintained. However, this requirement is subject to a series of complex factors, such as the uncertain train braking performance, train communication delay, and driver reaction time. In this paper, we propose a unified mathematical framework to analyze the safety‐oriented reliability of metro train timetables with different corridor capacities, that is, the train traffic density, and determine the most reliable train timetable for metro lines in an uncertain environment. By employing a space‐time network representation in the formulations, the reliability‐based train timetabling problem is formulated as a nonlinear stochastic programming model, in which we use 0‐1 variables to denote the time‐dependent velocity and position of all involved trains. Several reformulation techniques are developed to obtain an equivalent mixed integer programming model with quadratic constraints (MIQCP) that can be solved to optimality by some commercial solvers. To improve the computational efficiency of the MIQCP model, we develop a dual decomposition solution framework that decomposes the primal problem into several sets of subproblems by dualizing the coupling constraints across different samples. An exact dynamic programming combined with search space reduction strategies is also developed to solve the exact optimal solutions of these subproblems. Two sets of numerical experiments, which involve a relatively small‐scale case and a real‐world instance based on the operation data of the Beijing subway Changping Line are implemented to verify the effectiveness of the proposed approaches.     

空中多飞行器飞行轨迹优化数值仿真

针对空中多飞行器在复杂环境中飞行轨迹的多目标最优问题，分析了多飞行器飞行过程中各种可视和不可视约束条件。基于在回避威胁区前提下燃料消耗最少、飞行时间最短的综合性能指标，采用“多方法组合”思路，提出了改进动态规划法和多点边值法组合算法，并进行了仿真验证，大量C＋＋数值飞行仿真结果表明该算法能够在考虑外界复杂环境和飞行器各种约束条件下快速规划出空中多飞行器的最优飞行轨迹，该组合算法具有一定的实用性和创新性。     

多重优化的分布式无线覆盖探测算法

为满足无线通信网络信号覆盖有效性的实时实地可重复探测的需求,提出一种基于传感器网络的分布式无线覆盖探测算法。通过随机部署于目标区域内的无线传感器节点对无线通信网接收信号强度进行感知和预处理;利用变异函数构造新的BP神经网络目标函数,通过改进粒子群算法优化其初始权值和阈值;利用训练好的网络模型对存在探测盲区的目标区域进行插值估计,并联合传感器节点采集到的数据生成无线通信网络等信号强度线。仿真结果表明,所提算法比其他经典算法具有更高的精度,可有效探测目标区域无线通信网络的信号覆盖情况。