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马尔可夫过程是一种理论最完备、应用最广、最简单的随机过程。利用马尔可夫性质(即无后效性质)将问题变成数学模型称为马尔可夫模型。马尔可夫模型在运筹学和系统工程中有较多应用如可靠性理论、排队论等。系统工程中常用的有两类马尔可夫过程:离散的(或称马尔可夫链)及不连续的(状态离散、时间连续)马尔可夫过程。本文力图从系统工程应用角度对马尔可夫模型的性质、基本方程、运算方法等作通俗的介绍,并举例说明在系统工程中的应用。重点介绍:1,确定从一个状态到另一个状态的转移概率。2,t→(?)时稳定极限概率。并给出 n 步平稳转移概率及极限概率的算法流程图。
Markov process is a theory of the most complete, most widely used, the most simple random process. Using Markovian properties (ie, non-afterwards properties) to turn the problem into a mathematical model is called the Markov model. Markov model in operations research and systems engineering more applications such as reliability theory, queuing theory. There are two types of Markov processes commonly used in systems engineering: discrete (or Markov chain) and discontinuous (discrete-state, continuous-time) Markov processes. This article tries hard to introduce the character of Markov model systematically, the basic equation, the operation method and so on for the popular introduction, and gives an example to illustrate the application in the system engineering. Highlights: 1, determine the transition from one state to another state probability. 2, t → (?) Stability limit probability. The flow chart of the n-step steady transfer probability and limit probability is given.