移动式C3I机动路线选择多准则决策折衷对话算法

提出非劣路径和满意路径的概念,给出准则网络图满意路径问题的数学模型,利用多准则决策理论和方法,通过构造辅助问题,研究辅助问题和非劣路径的关系,设计出多准则网络图的交互式满意路径算法。     

m 序列完备递归采样值的存在条件

本文用群论方法讨论了n级m序列完备递归采样值的存在条件,证明了对任意n级m序列,其完备递归采样值存在的充要条件是商群G=Z_p~*/H(其中p=2~n—1,Z_p~*={s|(s,p)=1},H={1,2,2~2,…,2~(n-1))为循环群。在完备递归采样值存在的条件下,求出了完备递归采样值的个数为n.φ(φ(2~n—1)/n)。最后给出了递归采样值的一个重要性质。     

基于 Petri 网的决策组织结构设计

决策组织设计的首要问题是如何获得可行的组织结构。决策组织作为典型的分布式智能系统,利用Ｐｅｔｒｉ网生成其可行的组织结构是极广泛采用的方法,并已取得很多成果。该文是对这一领域的过去、现在和未来的综述。     

机械设备视情维修决策系统的研究与开发

从技术的角度讨论了为机械设备开发维修决策支持系统的必要性、可行性及系统技术关键的解决策略,以及系统开发中对人力资源的需求,为开发这样的系统提供技术与管理上的支持.     

Comparison of rank aggregation methods based on inherent ability

Ranking is a common task for selecting and evaluating alternatives. In the past few decades, combining rankings results from various sources into a consensus ranking has become an increasingly active research topic. In this study, we focus on the evaluation of rank aggregation methods. We first develop an experimental data generation method, which can provide ground truth ranking for alternatives based on their “inherent ability.” This experimental data generation method can generate the required individual synthetic rankings with adjustable accuracy and length. We propose characterizing the effectiveness of rank aggregation methods by calculating the Kendall tau distance between the aggregated ranking and the ground truth ranking. We then compare four classical rank aggregation methods and present some useful findings on the relative performances of the four methods. The results reveal that both the accuracy and length of individual rankings have a remarkable effect on the comparison results between rank aggregation methods. Our methods and results may be helpful to both researchers and decision‐makers.     

Augmented nested sampling for stochastic programs with recourse and endogenous uncertainty

We propose a novel simulation‐based approach for solving two‐stage stochastic programs with recourse and endogenous (decision dependent) uncertainty. The proposed augmented nested sampling approach recasts the stochastic optimization problem as a simulation problem by treating the decision variables as random. The optimal decision is obtained via the mode of the augmented probability model. We illustrate our methodology on a newsvendor problem with stock‐dependent uncertain demand both in single and multi‐item (news‐stand) cases. We provide performance comparisons with Markov chain Monte Carlo and traditional Monte Carlo simulation‐based optimization schemes. Finally, we conclude with directions for future research.     

移动通信网络位置群体节点的挖掘方法

对移动通信网络的位置群体节点进行了优化定位和挖掘,优化移动通信网络的覆盖度和可靠度,传统的位置群体节点挖掘算法采用信息度增益控制挖掘算法,算法不能自主感知节点信息数据的变化,无法实现数据信息的实时传递和决策。提出基于位置群体节点信息融合和滤波控制的移动通信网络位置群体节点的挖掘方法。构建移动通信网络节点的分布模型和信道模型,采用多径信道均衡设计实现位置群体节点信息融合,采用自适应滤波控制方法实现对通信节点挖掘的干扰抑制。仿真结果表明,采用该方法进行通信节点挖掘,信标定位准确,信号的覆盖度较合理,实现了信道空间的合理高效利用,实现了信道均衡和干扰抑制,有效降低了通信的误比特率。     

旋转单元电场矢量法的真解判定方法

旋转矢量法可被用来进行有源相控阵列的通道校准。每轮测试后在计算相应通道的幅相时会出现伪解。通过调整固定场矢量的幅度,进行两轮测试,判定两轮测试中绝对解不变的那组解为真解。其辨别方法,在有效判定真解的同时,也降低了计算量与测试量。另外,由于两轮测试时只需测量幅度信息,降低了测试设备复杂度。数值仿真结果证明了此方法的有效性。     

策略不确定条件下基于高阶超博弈的军事对抗决策方法

军事对抗决策中面临的一个主要问题是难以确定敌方的策略集。基于超博弈分析策略不确定条件下的军事对抗决策问题。在分析超博弈中信念迭代原理的基础上,提出了基于高阶超博弈的对抗决策方法。将高阶信念中的结果反思到低阶信念,并最终反思到一阶信念中,将己方的决策建立在对敌方可能决策的分析的基础上。使得己方的决策具有针对性且更加合理。以二战中西线战役为例验证了方法的可行性和有效性。     

弹炮混编防空群机动部署方案优选与评估

高技术条件下的反空袭作战中,弹炮混编防空群机动部署是相对传统防空作战中固定部署方式的一种新的部署方式,结合数学模型来确定机动部署的原则及部署方案的优化与评估。