文章基本信息

标题：Identifying Petri Nets with Silent Transitions by Event Traces Classification
本地全文：下载
作者：Yolanda Alvarez-Pérez ; Ernesto López-Mellado
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：4
页码：199-204
DOI：10.1016/j.ifacol.2021.04.052
语种：English
出版社：Elsevier
摘要：AbstractA method for discovering workflow nets (WFN) with silent transitions from a log of event tracesλis presented. It operates in two stages; in the first one,λis partitioned into three classes of traces: normal traces, short abnormal traces, and long abnormal traces. In the second stage, the normal traces are processed to build a WFN that may contain transitions of typeinitializeandfinalize;afterwards, this net is refined by adding the transitions of typeskipandredo,which are determined from the short abnormal traces and the long abnormal traces respectively. Implementation and tests are presented.
关键词：KeywordsDiscrete Event Process IdentificationSilent transitionsEvent log classification