基于马氏过程的电子对抗装备伺服驱动器可用度分析

针对电子对抗装备天线伺服系统驱动器可用度评估问题,考虑其具有优先使用权冷贮备冗余设计的特点,运用马尔可夫过程分析的方法,研究修理工人数不同情况下伺服驱动器稳态可用度和瞬时可用度,建立相应的数学模型,最后进行实例验证,绘出不同维修策略下系统瞬时可用度随时间变化的曲线.     

VLMC控制流软件可靠性度量方法

针对现有软件可靠性模型普遍不适用于实际软件的问题,分析了软件内部模块间控制转移机理,通过分离入口模块,提取一阶控制转移概率矩阵;弱化内部模块与出口模块间差异,重构二阶以上转移概率矩阵,在改进Cheung模型的基础上建立一个更符合软件实际的可靠性度量模型。针对变阶依赖（ VLMC）控制转移导致的可靠性度量难问题,通过对导致复杂依赖的多入多出模块进行节点扩展,将VLMC控制流转化为Markov链,利用所建立的软件可靠性模型对VLMC控制流软件进行可靠性度量。研究利用演绎推理对所建立模型进行了正确性形式化证明。最后给出了方法的实例验证。     

在非高斯马尔可夫噪声中的Robust检测

文中探讨了在仅已知噪声边缘分布族和相关系数的条件下非高斯马尔可夫噪声中确知信号的Robust检测问题。设噪声样本可表示为一阶AR过程:n_i=ρn_(i-1)+Y_i,(i=1,2,…,N),其中Y_i为独立同分布的随机序列。当p较小时,以检测器效验为性能指标并对ρ取一级和二级近似,分别得到了对应的有记忆和无记忆Robust检测器的结构。     

人才结构系统分析的目标规划方法

本文把马尔可夫过程和目标规划结合起来,提出人才结构系统分析的单项控制和多项控制,并在单项控制模型的基础上发展成了多项控制模型,加强了模型的可信度和通用性。     

最小、最大广义最优停止规则的特征

设(X_n,F_n)_1~∞是适应的报酬序列,(γ_n)是相应的snell 包,(A_n)是(γ_n)的Doob-Meyer 分解中零初值的可料增过程。本文继J.Klass 的研究证明了σ_1=inf{K≥1:X_k≥γ_k}是最小半最优的且是最大严格正则的广义规则,而K_0=sup{n≥0:A_n=0}<∞是最大正则的广义规则,从而得出了广义最优规则唯一性的另一表述。     

三态部件的可靠性分析

本文给出完备的三态部件的可靠性模型类。从静态的观点来看,三态部件的可靠性模型有两类：（１）成功,降格成功,失败;（２）成功,双失败。从动态的观点来看,考虑到三个状态之间的转化关系,其模型类相对复杂;但是在失败率λ、维修率μ为常数的条件下,只需六个参数（λ１λ２λ３μ１μ２μ３）,便可以用马尔可夫模型给出三态部件的可靠性统一模型,并给出部件在三状态的概率函数Ｐｉ（ｔ）的解析表达式（ｔ为时间,ｉ表示状态）。     

基于隐马尔可夫模型的IDS程序行为异常检测

提出一种新的基于隐马尔可夫模型的程序行为异常检测方法,此方法利用系统调用序列,并基于隐马尔可夫模型来描述程序行为,根据程序行为模式的出现频率对其进行分类,并将行为模式类型同隐马尔可夫模型的状态联系在一起。由于各状态对应的观测值集合互不相交,模型训练中采用了运算量较小的序列匹配方法,与传统的Baum Welch算法相比,训练时间有较大幅度的降低。考虑到模型中状态的特殊含义以及程序行为的特点,将加窗平滑后的状态序列出现概率作为判决依据。实验表明,此方法具有很高的检测准确性,其检测效率也优于同类方法。     

Analysis of artillery shoot‐and‐scoot tactics

Firing multiple artillery rounds from the same location has two main benefits: a high rate of fire at the enemy and improved accuracy as the shooter's aim adjusts to previous rounds. However, firing repeatedly from the same location carries significant risk that the enemy will detect the artillery's location. Therefore, the shooter may periodically move locations to avoid counter‐battery fire. This maneuver is known as the shoot‐and‐scoot tactic. This article analyzes the shoot‐and‐scoot tactic for a time‐critical mission using Markov models. We compute optimal move policies and develop heuristics for more complex and realistic settings. Spending a reasonable amount of time firing multiple shots from the same location is often preferable to moving immediately after firing an initial salvo. Moving frequently reduces risk to the artillery, but also limits the artillery's ability to inflict damage on the enemy.     

Aggregating courier deliveries

We consider the problem of efficiently scheduling deliveries by an uncapacitated courier from a central location under online arrivals. We consider both adversary‐controlled and Poisson arrival processes. In the adversarial setting we provide a randomized (3βΔ/2δ ? 1) ‐competitive algorithm, where β is the approximation ratio of the traveling salesman problem, δ is the minimum distance between the central location and any customer, and Δ is the length of the optimal traveling salesman tour overall customer locations and the central location. We provide instances showing that this analysis is tight. We also prove a 1 + 0.271Δ/δ lower‐bound on the competitive ratio of any algorithm in this setting. In the Poisson setting, we relax our assumption of deterministic travel times by assuming that travel times are distributed with a mean equal to the excursion length. We prove that optimal policies in this setting follow a threshold structure and describe this structure. For the half‐line metric space we bound the performance of the randomized algorithm in the Poisson setting, and show through numerical experiments that the performance of the algorithm is often much better than this bound.     

动态武器目标分配问题的马尔可夫性

动态武器目标分配(weapon target assignment,WTA)问题是军事运筹学研究的重要理论问题,也是作战指挥决策中迫切需要解决的现实问题。在对动态WTA问题进行描述分析的基础上,运用随机过程理论证明了动态WTA过程的马尔可夫性;给出了该马尔可夫决策过程的状态转移概率的解析表达式,并对其状态特点进行了简要分析。研究结果可以为动态WTA及相关问题的研究提供理论和方法依据。