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随机Ｐｅｔｒｉ网和马尔可夫链有着内在的联系，用它来对状态整体的变化规律不十分明确但状态分量的变化规律明确的一类问题建模，为马尔可夫预测模型的应用提供了方便。
Stochastic Petri nets and Markov chains are intrinsically linked. Using it to model a class of problems whose law of variation of the whole state is not clear but the law of change of the state component is clear, it provides convenience for the application of Markov forecasting model .