Folding Marked Generalized Stochastic Petri Nets for Time Prediction in Business Processes
Abstract
Generalized 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.
- Citation
- BibTeX
Fahrenkrog-Petersen, S. A. & Weidlich, M.,
(2018).
Folding Marked Generalized Stochastic Petri Nets for Time Prediction in Business Processes.
In:
Czarnecki, C., Brockmann, C., Sultanow, E., Koschmider, A. & Selzer, A.
(Hrsg.),
Workshops der
INFORMATIK 2018 -
Architekturen, Prozesse,
Sicherheit und Nachhaltigkeit.
Bonn:
Köllen Druck+Verlag GmbH.
(S. 239-244).
@inproceedings{mci/Fahrenkrog-Petersen2018,
author = {Fahrenkrog-Petersen, Stephan A. AND Weidlich, Matthias},
title = {Folding Marked Generalized Stochastic Petri Nets for Time Prediction in Business Processes},
booktitle = {Workshops der INFORMATIK 2018 - Architekturen, Prozesse, Sicherheit und Nachhaltigkeit},
year = {2018},
editor = {Czarnecki, Christian AND Brockmann, Carsten AND Sultanow, Eldar AND Koschmider, Agnes AND Selzer, Annika} ,
pages = { 239-244 },
publisher = {Köllen Druck+Verlag GmbH},
address = {Bonn}
}
author = {Fahrenkrog-Petersen, Stephan A. AND Weidlich, Matthias},
title = {Folding Marked Generalized Stochastic Petri Nets for Time Prediction in Business Processes},
booktitle = {Workshops der INFORMATIK 2018 - Architekturen, Prozesse, Sicherheit und Nachhaltigkeit},
year = {2018},
editor = {Czarnecki, Christian AND Brockmann, Carsten AND Sultanow, Eldar AND Koschmider, Agnes AND Selzer, Annika} ,
pages = { 239-244 },
publisher = {Köllen Druck+Verlag GmbH},
address = {Bonn}
}
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More Info
ISBN: 978-3-88579-679-4
ISSN: 1617-5468
xmlui.MetaDataDisplay.field.date: 2018
Language:
(en)

Content Type: Text/Conference Paper