基于D-S证据理论的机载雷达模糊识别方法

针对机载雷达信号的复杂性和模糊性等特点,提出一种D-S(登普斯特-谢弗)证据理论和模糊理论组合应用的方法用于对机载雷达的识别。通过对信号的积累和对信任度(模糊隶属度)的重新分配,有效地解决了机载雷达信号的不确定性问题以及如何利用信号在时间上的冗余信息问题,提高了信号的正确识别率。仿真实验和正确识别率的统计结果验证了这种方法十分有效。     

一种航天侦察任务-资源匹配的负载均衡方法

当前航天侦察任务预处理方法一般仅从任务需求的角度考虑资源分配问题,容易导致负载不均衡,对此提出了一种综合考虑任务需求与资源负载的任务-资源匹配方法.分析了资源负载均衡需要考虑的任务要素以及相应的描述方法,提出用任务执行概率度量卫星资源负载状况,基于任务流模型给出了单任务执行概率的估算公式,并给出了一种简易的多任务执行概...     

Case‐based reasoning and improved adaptive search for project scheduling

Most scheduling problems are notoriously intractable, so the majority of algorithms for them are heuristic in nature. Priority rule‐based methods still constitute the most important class of these heuristics. Of these, in turn, parametrized biased random sampling methods have attracted particular interest, due to the fact that they outperform all other priority rule‐based methods known. Yet, even the “best” such algorithms are unable to relate to the full range of instances of a problem: Usually there will exist instances on which other algorithms do better. We maintain that asking for the one best algorithm for a problem may be asking too much. The recently proposed concept of control schemes, which refers to algorithmic schemes allowing to steer parametrized algorithms, opens up ways to refine existing algorithms in this regard and improve their effectiveness considerably. We extend this approach by integrating heuristics and case‐based reasoning (CBR), an approach that has been successfully used in artificial intelligence applications. Using the resource‐constrained project scheduling problem as a vehicle, we describe how to devise such a CBR system, systematically analyzing the effect of several criteria on algorithmic performance. Extensive computational results validate the efficacy of our approach and reveal a performance similar or close to state‐of‐the‐art heuristics. In addition, the analysis undertaken provides new insight into the behaviour of a wide class of scheduling heuristics. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 201–222, 2000     

A specially structured nonlinear integer resource allocation problem

We present an algorithm for solving a specially structured nonlinear integer resource allocation problem. This problem was motivated by a capacity planning study done at a large Health Maintenance Organization in Texas. Specifically, we focus on a class of nonlinear resource allocation problems that involve the minimization of a convex function over one general convex constraint, a set of block diagonal convex constraints, and bounds on the integer variables. The continuous variable problem is also considered. The continuous problem is solved by taking advantage of the structure of the Karush‐Kuhn‐Tucker (KKT) conditions. This method for solving the continuous problem is then incorporated in a branch and bound algorithm to solve the integer problem. Various reoptimization results, multiplier bounding results, and heuristics are used to improve the efficiency of the algorithms. We show how the algorithms can be extended to obtain a globally optimal solution to the nonconvex version of the problem. We further show that the methods can be applied to problems in production planning and financial optimization. Extensive computational testing of the algorithms is reported for a variety of applications on continuous problems with up to 1,000,000 variables and integer problems with up to 1000 variables. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 770–792, 2003.     

一种新型的不精确推理——SCESS不精确推理

本文是以模糊数学理论为基础,并考虑了人的心理因素,构造出一种新型的不精确推理。它已在一个实用的专家系统——突发性案件专家支持系统(SCESS)中得到实现。该推理能处理用单个数值、模糊区间和自然语言描述的不精确知识的可信度,并通过用户的态度得出相应的结论。     

基于模糊集和证据推理方法的武器系统可靠性评估

提出了一种评估武器系统可靠性的新方法。在这种方法中,武器系统中各组成部分及零部件的可靠性用模糊语言变量来表示,利用证据推理方法合成各子系统零部件的可靠性评估结果,提高了各子系统的可靠性水平。文中以某高炮系统的可靠性评估阐述了该方法的应用情况     

基于规则控制的快速高度跟踪算法

提出一种全新的基于模糊推理与规则控制的高度跟踪算法。这种算法无论是在跟踪效果与运算速度上都大大优于以往的最速下降法、动态规划法、最优控制法等,而且可以对最大俯仰角、最大可用过载、希望跟踪程度等跟踪参数进行随意设定。大量的仿真计算证明,该算法具有很好的实时性、收敛性及可扩展性。可以极大地减轻对地攻击低空轨迹规划的工作,对巡航导弹、无人机更具应用价值     

基于军民融合的军事信息资源效能转化

军事信息资源效能转化的强弱,事关军队信息化建设和军队战斗力生成,需要引起高度重视。本文阐述军民融合对军事信息效能转化工作的巨大推动力,并通过分析当前制约军民融合军事信息资源效能转化的内因和外因,提出完善军民融合军事信息资源效能转化工作的措施建议。     

集中控制混合网络中基于流的资源分配算法

集中控制混合网络中,异构化网络内部的流量具有一定的规律和特性,如果使用原有的单一的离散式最大极值和无状态的网络资源调度算法,忽略了异构网络规律,会造成网络利用率较低、易震荡、部分网络流延迟等问题。通过分析由集中控制网络和普通网络组成的混合网络的拓扑结构,对混合网络结构中常见问题如流闪现、不能估计的流、路径堵塞或连接震荡场景进行分析,并提出基于期望和状态的流量评价资源规划算法POS和POS-FME。算法考虑混合网络的运行状态,对系统可用资源进行评估,为系统中各种流匹配对应可用资源,并具有一定的预测作用,从而避免混合网络出现运行效率低下的场景。通过实验,POS算法和POS-FME算法相对传统算法,利用率提高了10%～30%,并降低了震荡和平均延迟。     

基于XML／RDF的油料装备模块化协同设计网格主体资源表达

针对协同设计网格中油料装备模块化协同设计主体资源规范化表达问题,提出按照模块设计能力划分油料装备模块化协同设计主体资源的分类体系,给出油料装备模块化协同设计主体资源的信息描述模型。在此基础上,采用元数据完成了油料装备模块化协同设计主体资源描述的元数据集的定义,并采用可扩展的资源描述框架RDF实现了元数据集的描述,规范了具有值域要求属性的赋值空间,给出了基于元数据集的油料装备模块化协同设计主体资源的RDF描述方法,解决了协同设计网格中统一完整和无二义性地描述资源对象的问题,并提出了利用资源表达向导的策略,规范和简化了资源主体的资源表达。