一种基于加权隐马尔可夫的 自回归状态预测模型

针对电子系统状态趋势预测问题,提出了一种加权隐马尔可夫模型的自回归趋势预测方法.该方法以自回归模型作为隐马尔可夫的状态输出,利用加权预测思想对马尔可夫链中的隐状态进行混合高斯模型的加权序列预测,并利用最大概率隐状态下的自回归系数计算模型输出.通过对实际的复杂混沌序列和电子系统BIT状态数据进行趋势预测,并针对不同模型参数下的预测结果进行实验分析,结果表明该方法对系统状态变化的趋势具有较好的预测性能.     

面向恶意程序传播的传感网可靠度评估

为评估恶意程序传播环境中的传感网可靠度,引入"死亡"状态扩展了传统的SEIR传染病模型,采用马尔可夫链确切地描述了传感节点的状态动态变化过程.利用随机博弈,提出了传感网恶意程序传播检测模型来预测恶意程序的传播行为概率,再将得到的结果整合到马尔可夫链的状态转换矩阵,实现了恶意程序传播故意性和马尔可夫链随机性的关联.建立了利用马尔可夫链计算恶意程序传播环境中传感节点可靠度的公式,分别给出了具有星形和簇状拓扑结构的传感网可靠度评估方法.实验给出了恶意程序传播对传感节点可靠度的影响,结果表明所提出的方法能有效评估整个传感网的可靠度.     

基于马尔可夫过程的UPS可靠性指标的计算

不间断电源(UPS)是在电网异常的情况下不间断地为电器负载设备提供后备交流电源,以维持电器正常运作的设备,目前其已在诸多领域中得到了广泛的应用.因此,基于六性协同工作平台的马尔可夫过程模块对某UPS系统的可靠性指标进行了认证和分析.首先,简单地介绍了UPS系统及其可靠性建模方法;其次,概述了可维修系统的马尔可夫过程求解;然后,阐述了六性协同工作平台和马尔可夫过程模块;最后,对利用六性协同工作平台的马尔可夫过程模块计算UPS系统可靠性指标的具体过程进行了详细的介绍,对于快速地求解UPS系统的可靠性水平具有重要的意义.     

面向智能交通的大数据实时分析技术

文中研究了基于改进马尔可夫链的交通流量预测方法，旨在利用大数据实时分析技术实现智能交通。首先，指出了交通流量预测在智能交通系统中的重要性和面临的挑战。随后，详细阐述了高阶多元马尔可夫链模型的理论基础，包括马尔可夫链的概念和高阶模型的扩展，从而提出了改进马尔可夫链的交通流量预测方法的总体架构。在此基础上，利用METR-LA数据集进行实验分析，对数据进行预处理和模型训练，并进行模型评估和数据分析。实验结果表明，改进后的马尔可夫链模型在交通流量预测方面具有一定的准确性和实用性。     

运用“大成智慧工程“对导弹系统贮存可靠性预测分析

本文对“大成智慧工程”作了简要的介绍，在此基础上分析了“大成智慧工程”在战略导弹武器系统贮存可靠性预测分析中的具体应用，并以某型战略导弹武器系统为例，给出了应用结果，模型运行结果可为战略导弹武器系统贮存可靠性管理提供科学依据，对灰色马尔可夫预测模型的建模机制及如何提高组合预测法的预测精度也作了积极的探讨。     

隐马尔可夫模型应用于入侵检测系统的研究

现在入侵检测系统面临着巨大挑战，越来越复杂的计算机网络系统，越来越高明的入侵手段要求入侵检测技术不断快速向前发展。对于入侵检测的实现手段也要多样化。 本文提出了一种基于隐马尔可夫模型的异常检测新方法——隐马尔可夫状态时延序列嵌入法（HMMTide）。这种方法的主要思想是用HMM模型的隐含状态序列的局部模型，即隐马尔可夫状态短序列，实现对正常行为的特征的刻画。通过对被测行为产生的隐马尔科夫状态序列局部模式与已建立的正常模型进行比较实现异常检测。该方法具有从不完整的数据中进行异常分析的能力，减少了对系统资源的需求。对HMMTjde方法进行了仿真实验，实验结果表明采用HMM方法后，虚警率大大降低了，而且在构建正常行为特征库时，对数据完整性的要求也大大降低了。     

基于马尔可夫过程的卫星移动信道模型及长期预测方法

卫星移动信道可被描述为基于有限状态马尔可夫过程的衰落模型,该文分析了卫星信道的可预测性,然后基于加权预测思想提出了一种卫星移动信道长期预测方法,该方法在当前信道采样的基础上进行二次采样,采样频率大于马尔可夫状态转移速率的2倍,利用信道状态的相关性和信道状态转移概率信息来加权预测未来长期内的信道状态,并依据自回归预测模型给出信道预测输出值,仿真结果表明,采用此方法对卫星信道未来的信道状态进行预测,在信噪比较高时均方误差能够达到10-2量级,在自适应传输过程中可以降低系统平均误比特率,且能够提高系统吞吐量性能,这对卫星移动通信系统的自适应传输和自适应资源分配都具有一定的指导意义。     

基于叠加马尔可夫链的4G流量订购量分析与预测

针对马尔可夫链预测的局限性,本文提出了能够定量计算叠加4G流量订购量的马尔可夫链预测方法.以定西地区2月4G流量订购量进行状态分级,划分为滞销、偏滞销、一般、偏畅销和畅销,计算状态转移矩阵,将不同步长转移矩阵求得的预测值进行加权平均,并运用叠加马尔可夫链方法建立该地区4G流量订购量模型,分析拟合结果.结果表明,该模型的预测精度达到了87.99％,预测效果较好,为4G流量订购量的预测提供了一种方法.     

基于小波隐性马尔可夫模型的人脸检测

本文提出了一种基于小波隐性马尔可夫模型(WHMM)的人脸检测方法,根据隐性马尔可夫模型对人脸拓扑结构的约束以及小波变换的多尺度性和局部定位性,采用3状态的WHMM进行从粗到精的人脸检测。实验结果表明这种方法具有较高的检测速度与正确率及鲁棒性。     

容错导航系统可靠性分析及发展

容错导航系统的可靠性分析是容错导航系统设计过程中最重要的步骤之一。随着近１０几年来容错控制技术的发展，对容错导航系统可靠性的分析也在不断地发展和得到进一步完善。从组合分析ＭｏｎｔｅＣａｒｌｏ仿真方法马尔可夫模型和半马尔可夫模型方法，容错系统的可靠性分析方法的适用范围正在逐渐扩大，也愈来愈会合实际系统的需要，但同时仍有许多问题需要解决。     

Numerical methods for reliability evaluation of Markov closedfault-tolerant systems

This paper compares three numerical methods for reliability calculation of Markov, closed, fault-tolerant systems which give rise to continuous-time, time-homogeneous, finite-state, acyclic Markov chains. The authors consider a modified version of Jensen's method (a probabilistic method, also known as uniformization or randomization), a new version of ACE (acyclic Markov chain evaluator) algorithm with several enhancements, and a third-order implicit Runge-Kutta method (an ordinary-differential-equation solution method). Modifications to Jensen's method include incorporating stable calculation of Poisson probabilities and steady-state detection of the underlying discrete-time Markov chain. The new version of Jensen's method is not only more efficient but yields more accurate results. Modifications to ACE algorithm are proposed which incorporate scaling and other refinements to make it more stable and accurate. However, the new version no longer yields solution symbolic with respect to time variable. Implicit Runge-Kutta method can exploit the acyclic structure of the Markov chain and therefore becomes more efficient. All three methods are implemented. Several reliability models are numerically solved using these methods and the results are compared on the basis of accuracy and computation cost     

Failure correlation in software reliability models

Perhaps the most stringent restriction in most software reliability models is the assumption of statistical independence among successive software failures. The authors research was motivated by the fact that although there are practical situations in which this assumption could be easily violated, much of the published literature on software reliability modeling does not seriously address this issue. The research work in this paper is devoted to developing the software reliability modeling framework that can consider the phenomena of failure correlation and to study its effects on the software reliability measures. The important property of the developed Markov renewal modeling approach is its flexibility. It allows construction of the software reliability model in both discrete time and continuous time, and (depending on the goals) to base the analysis either on Markov chain theory or on renewal process theory. Thus, their modeling approach is an important step toward more consistent and realistic modeling of software reliability. It can be related to existing software reliability growth models. Many input-domain and time-domain models can be derived as special cases under the assumption of failure s-independence. This paper aims at showing that the classical software reliability theory can be extended to consider a sequence of possibly s-dependent software runs, viz, failure correlation. It does not deal with inference nor with predictions, per se. For the model to be fully specified and applied to estimations and predictions in real software development projects, we need to address many research issues, e.g., the detailed assumptions about the nature of the overall reliability growth, way modeling-parameters change as a result of the fault-removal attempts     

简化Markov模型的可靠性分析

Markov模型是电子产品系统可靠性分析中最常使用的方法。但在应用Markov模型的时候一个主要的问题是它的巨大的状态数，使得它对复杂系统的建模和分析变得非常困难。本文提出了一种新的简化Markov模型的方法来简化对系统可靠性的分析。并且对该简化方法的误差界限进行了讨论。数值仿真结果表明了该方法的有效性。     

Quantitative Reliability Evaluation of Repairable Phased-Mission Systems Using Markov Approach

A quantitative reliability model for a phased mission system is developed using a Markov process. Two cases for the mission-phase change times are assumed: 1) to be known in advance and 2) to be random variables. A method of solution is presented and illustrated by examples. The solution of phased-mission systems is equivalent to solving a sequence of uni-phase systems with appropriate initial conditions.     

Markov模型在功能安全温度变送器的应用

针对如何分析功能安全产品的可靠性问题,提出了一种基于Markov模型的可靠性分析方法。通过对产品的系统结构进行分析,研究系统的 Markov状态转移图,结合失效模式、影响及其诊断分析(FMEDA)法对系统进行可靠性建模,引入状态转移矩阵,并以功能安全温度变送器为例对模型进行验证。相关验证结果表明,该模型应用于功能安全领域是可行的。     

Characterization and estimation of two-dimensional ARMA models

A class of finite-order two-dimensional autoregressive moving average (ARMA) is introduced that can represent any process with rational spectral density. In this model the driving noise is correlated and need not be Gaussian. Currently known classes of ARMA models or AR models are shown to be subsets of the above class. The three definitions of Markov property are discussed, and the class of ARMA models are precisely stated which have the noncausal and semicausal Markov property without imposing any specific boundary conditions. Next two approaches are considered to estimate the parameters of a model to fit a given image. The first method uses only the empirical correlations and involves the solution of linear equations. The second method is the likelihood approach. Since the exact likelihood function is difficult to compute, we resort to approximations suggested by the toroidal models. Numerical experiments compare the quality of the two estimation schemes. Finally the problem of synthesizing a texture obeying an ARMA model is considered.     

一类分布式传感器网络的FNN Markov可靠性模型

针对分布式传感器网络中故障点多、可靠性参数估计困难的特点,文章提出了一种基于模糊神经网络的Markov可靠性模型。仿真结果表明,神经网络收敛时的可用度与Markov模型计算值的相对误差在数量级,从而验证了所提模型的正确性。     

Approximate steady-state solutions for Markov systems based upon the transition-rate matrix deviation concept

This paper derives an approximate method for solving the steady-state Markov equations. The approximate solutions are determined using the known or easily obtainable solutions of a Markov system whose transition-rate matrix slightly differs from that of the original system. The method suggested makes it possible to derive approximate analytic expressions for the steady-state probabilities of system states and associated reliability indices and/or to calculate their numerical values. The expressions for the error bounds for the method are provided. The method is applied to derive expressions for the state probabilities of two transmission lines sharing the same right of way and exposed to common cause failures, as a demonstration.     

Analysis of a composite performance reliability evaluation for Markovian queueing systems

This paper considers analytical techniques for the evaluation of reliability, availability and combined performance and reliability measures. Markov models are common tools for system reliability evaluation. In this paper, we first compute the state probabilities of Markov model behaviour. We then investigate expected values of interval availability measures. The method is simple and easy to implement, yet very effective in dealing with the problem of computer systems.