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Folding Marked Generalized Stochastic Petri Nets for Time Prediction in Business Processes

dc.contributor.authorFahrenkrog-Petersen, Stephan A.
dc.contributor.authorWeidlich, Matthias
dc.contributor.editorCzarnecki, Christian
dc.contributor.editorBrockmann, Carsten
dc.contributor.editorSultanow, Eldar
dc.contributor.editorKoschmider, Agnes
dc.contributor.editorSelzer, Annika
dc.date.accessioned2018-10-10T10:43:43Z
dc.date.available2018-10-10T10:43:43Z
dc.date.issued2018
dc.description.abstractGeneralized Stochastic Petri Nets (GSPNs) can be used for performance analysis of business processes. Recently, it was shown that foldings of a GSPN, i.e., a set of model reduction rules, help to avoid over-fitting of the model with respect to the performance characteristics of a process. Yet, these foldings ignore the marking of a GSPN and, thus, are applicable solely for steady-state analysis. In this paper, we discuss how foldings may be lifted to marked nets and provide an assessment of stateful foldings for sequential GSPNs.en
dc.identifier.isbn978-3-88579-679-4
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/17224
dc.language.isoen
dc.publisherKöllen Druck+Verlag GmbH
dc.relation.ispartofWorkshops der INFORMATIK 2018 - Architekturen, Prozesse, Sicherheit und Nachhaltigkeit
dc.relation.ispartofseriesLecture Notes in Informatics
dc.subjectBusiness Process Management
dc.subjectProcess Mining
dc.subjectGeneralized Stochastic Petri nets
dc.subjectModel Simplification
dc.titleFolding Marked Generalized Stochastic Petri Nets for Time Prediction in Business Processesen
dc.typeText/Conference Paper
gi.citation.endPage244
gi.citation.publisherPlaceBonn
gi.citation.startPage239
gi.conference.date26.-27.09.2018
gi.conference.locationBerlin
gi.conference.sessiontitleZuGPM 2018 – Workshop zum Stand, den Herausforderungen und Impulsen des Geschäftsprozessmanagements

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