This paper addresses the problem of discovering a Petri Net (PN) from a long event sequence representing the behavior of discrete-event processes. A method for building a 1-bounded PN able to execute the events sequence S is presented; it is based on determining causality and concurrence relations between events and computing the t-invariants. This novel method determines the structure and the initial marking of an ordinary PN, which reproduces the behavior in S. The algorithms derived from the method are efficient and have been implemented and tested on numerous examples of diverse complexity.

中文翻译：

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通过计算 T 不变量发现离散事件过程的 Petri 网模型


本文解决了从表示离散事件过程行为的长事件序列中发现 Petri 网 (PN) 的问题。提出了一种构建能够执行事件序列 S 的 1 有界 PN 的方法；它基于确定事件之间的因果关系和并发关系并计算 t 不变量。这种新颖的方法确定了普通 PN 的结构和初始标记，从而重现了 S 中的行为。从该方法导出的算法非常高效，并且已经在许多不同复杂性的示例上进行了实现和测试。