基于类吸收壁的马尔科夫链模型及其应用  

Markov Chain Model Based on Similar Absorbing Barrier and Its Application

作　　者：代娟 吕王勇[1,2] 陈雯 李思奇 Dai Juan;Lyu Wangyong;Chen Wen;Li Siqi(School of Mathematical Sciences,Sichuan Normal University,Chengdu 610068,China;Visual Computing and Virtual Reality Key Laboratory of Sichuan Province,Chengdu 610068,China)

机构地区：[1]四川师范大学数学科学学院 [2]可视化计算与虚拟现实四川省重点实验室,成都610068

出　　处：《统计与决策》2021年第17期61-65,共5页Statistics & Decision

摘　　要：文章首先针对离散参数马尔科夫链定义中各状态的特点,定义一个状态集,构造了一个新的基于类吸收壁的马尔科夫链模型,并对这个模型的性质进行推导和研究。然后通过预设约定状态发生的概率,计算该状态发生的最晚时间,从而达到提早预防、高效抽查等效果。最后利用该模型对生产男裤的机器的运作状态进行分析,证明了模型的有效性。This paper firstly defines a state set according to the characteristics of each state in the definition of discrete parameter Markov chain, constructs a new Markov chain model based on the similar absorbing barrier, and deduces and studies the properties of this model. Then, by presetting the probability of occurrence of the agreed state, the paper calculates the latest time of occurrence of the state, so as to achieve early prevention, efficient spot check and other effects. Finally, the model is used to analyze the operation state of the machine to produce men’s trousers, which proves the validity of the model.

关 键 词：马尔科夫链 类吸收壁 条件概率 C-K方程 

分 类 号：O211.9[理学—概率论与数理统计]