基于Vague集的TOPSIS法求解目标优先级

针对传感器管理中目标—传感器配对出现的目标优先级求解问题,提出了一种基于Vague集的TOPSIS计算方法。在分析目标优先级的主要影响因素基础上,定义了各影响因素的影响系数。同时结合Vague集的TOPSIS法给出了目标优先级的计算步骤,为目标优先级求解提供了一种新途径。并结合仿真算例表明该方法的合理性与有效性。     

基于本体的消防应急决策模型

消防信息技术研究的不断深入和本体论在计算机中的应用日益成熟,促进了人工智能系统的发展。以消防应急决策过程为研究背景,尝试将全局数据包络分析引入应急决策中,建立消防应急管理协作模型,分析多个决策结果的相对有效性,协助决策者在较短时间里作出合理的决策。     

时间管理在实时仿真中的改进

时问是分布仿真中的核心概念;时间管理是分布交互仿真的关键技术.探讨了分布交互仿真中高层体系结构(HLA)的时间管理机制,针对HLA在实时系统仿真方面的不足,分析其原因,提出了时间管理在实时仿真中的改进方法,对HLA在实时系统仿真中的应用有一定的参考价值.     

Technical note: Finite-time regret analysis of Kiefer-Wolfowitz stochastic approximation algorithm and nonparametric multi-product dynamic pricing with unknown demand

We consider the problem of nonparametric multi-product dynamic pricing with unknown demand and show that the problem may be formulated as an online model-free stochastic program, which can be solved by the classical Kiefer-Wolfowitz stochastic approximation (KWSA) algorithm. We prove that the expected cumulative regret of the KWSA algorithm is bounded above by where κ₁, κ₂ are positive constants and T is the number of periods for any T = 1, 2, … . Therefore, the regret of the KWSA algorithm grows in the order of , which achieves the lower bounds known for parametric dynamic pricing problems and shows that the nonparametric problems are not necessarily more difficult to solve than the parametric ones. Numerical experiments further demonstrate the effectiveness and efficiency of our proposed KW pricing policy by comparing with some pricing policies in the literature.     

面向多核网络分组处理系统的线程亲和缓冲区管理机制

基于通用多核架构的网络分组处理系统性能受到诸如分组IO开销高、多核共享内存及进程调度竞争大、页表缓冲表项失效率高等问题的困扰。为此提出一种基于通用多核网络分组处理系统、面向高速分组转发应用的线程亲和缓冲区硬件管理机制,并在网络专用协处理引擎上实现。该机制采用无中断的线程亲和调度策略,将包含控制信息与缓冲区地址信息的描述符和分组数据按照分组处理的线程号链式地对应加载在多个地址连续的共享缓冲区中。基于通用多核和现场可编程门阵列平台进行报文转发测试,实验结果表明,采用线程亲和缓冲区管理机制能使平均报文转发处理性能提升12.4%,有效地降低IO开销和TLB表项失效率。     

Value management of diagnostic equipment with cancelation,no‐show,and emergency patients

Magnetic resonance imaging and other multifunctional diagnostic facilities, which are considered as scarce resources of hospitals, typically provide services to patients with different medical needs. This article examines the admission policies during the appointment management of such facilities. We consider two categories of patients: regular patients who are scheduled in advance through an appointment system and emergency patients with randomly generated demands during the workday that must be served as soon as possible. According to the actual medical needs of patients, regular patients are segmented into multiple classes with different cancelation rates, no‐show probabilities, unit value contributions, and average service times. Management makes admission decisions on whether or not to accept a service request from a regular patient during the booking horizon to improve the overall value that could be generated during the workday. The decisions should be made by considering the cancelation and no‐show behavior of booked patients as well as the emergency patients that would have to be served because any overtime service would lead to higher costs. We studied the optimal admission decision using a continuous‐time discrete‐state dynamic programming model. Identifying an optimal policy for this discrete model is analytically intractable and numerically inefficient because the state is multidimensional and infinite. We propose to study a deterministic counterpart of the problem (i.e., the fluid control problem) and to develop a time‐based fluid policy that is shown to be asymptotically optimal for large‐scale problems. Furthermore, we propose to adopt a mixed fluid policy that is developed based on the information obtained from the fluid control problem. Numerical experiments demonstrate that this improved policy works effectively for small‐scale problems. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 287–304, 2016     

武器系统研制单位管理水平的贝叶斯评估分析

将Bayes理论应用于对武器系统研制单位管理水平的评估.克服了验前评估方法主观性大的缺陷,充分利用收集到的补充信息,对评估结果作了后验预分析,得到了更加可信的评估结论,从而改进了决策过程.     

车辆悬挂系统的主动优化控制器设计及仿真

基于特征结构配置参数化结果,提出了车辆悬挂系统的主动优化控制器设计方法。该方法直接基于车辆悬挂系统的参数矩阵,便于工程应用。车辆悬挂系统的仿真实例表明所提主动优化控制器设计方法简单且有效。     

一种基于多层次网格的高效相关过滤方法

在分布式仿真系统中 ,网上流动的大量冗余数据严重影响了系统的可伸缩性。基于均匀网格的相关过滤法减少了冗余数据 ,但具有匹配不精确 ,格子尺寸单一 ,难以适应所有实体的缺点。提出了一种基于多层次网格的相关过滤方法 ,克服了均匀网格法的上述缺点 ,并继承了均匀网格法处理速度快的特点 ,具有快速灵活的特点     

MUOS网络管理与控制技术的研究

介绍了美军移动用户目标系统MUOS(Mobile User Objective System),分析和总结了该系统下网络管理体系结构和运行机制,并就其实现中的关键技术进行了深入研究,得到了一些对我国有借鉴意义的结论。