A Monitoring Approach Based on Fuzzy Stochastic P-Timed Petri Nets of a Railway Transport Network
This paper proposes a monitoring approach based on stochastic fuzzy Petri nets (SFPNs) for railway transport networks. In railway transport, the time factor is a critical parameter as it includes constraints to avoid overlaps, delays, and collisions between trains. The temporal uncertainties and con...
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2021-01-01
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Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2021/5595065 |
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doaj-557817e5f56e4d3fb174fcab6c3808132021-05-10T00:27:18ZengHindawi-WileyJournal of Advanced Transportation2042-31952021-01-01202110.1155/2021/5595065A Monitoring Approach Based on Fuzzy Stochastic P-Timed Petri Nets of a Railway Transport NetworkAnis M’hala0Laboratory of AutomationThis paper proposes a monitoring approach based on stochastic fuzzy Petri nets (SFPNs) for railway transport networks. In railway transport, the time factor is a critical parameter as it includes constraints to avoid overlaps, delays, and collisions between trains. The temporal uncertainties and constraints that may arise on the railway network may degrade the planned schedules and consequently affect the availability of the transportation system. This leads to many problems in the decision and optimization of the railway transport systems. In this context, we propose a new fuzzy stochastic Petri nets for monitoring (SFPNM). The main goal of the proposed supervision approach is to allow an early detection of traffic disturbance to avoid catastrophic scenarios and preserve stability and security of the studied railway networks. Finally, to demonstrate the effectiveness and accuracy of the approach, an application to the case study of the Tunisian railway network is outlined.http://dx.doi.org/10.1155/2021/5595065 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Anis M’hala |
spellingShingle |
Anis M’hala A Monitoring Approach Based on Fuzzy Stochastic P-Timed Petri Nets of a Railway Transport Network Journal of Advanced Transportation |
author_facet |
Anis M’hala |
author_sort |
Anis M’hala |
title |
A Monitoring Approach Based on Fuzzy Stochastic P-Timed Petri Nets of a Railway Transport Network |
title_short |
A Monitoring Approach Based on Fuzzy Stochastic P-Timed Petri Nets of a Railway Transport Network |
title_full |
A Monitoring Approach Based on Fuzzy Stochastic P-Timed Petri Nets of a Railway Transport Network |
title_fullStr |
A Monitoring Approach Based on Fuzzy Stochastic P-Timed Petri Nets of a Railway Transport Network |
title_full_unstemmed |
A Monitoring Approach Based on Fuzzy Stochastic P-Timed Petri Nets of a Railway Transport Network |
title_sort |
monitoring approach based on fuzzy stochastic p-timed petri nets of a railway transport network |
publisher |
Hindawi-Wiley |
series |
Journal of Advanced Transportation |
issn |
2042-3195 |
publishDate |
2021-01-01 |
description |
This paper proposes a monitoring approach based on stochastic fuzzy Petri nets (SFPNs) for railway transport networks. In railway transport, the time factor is a critical parameter as it includes constraints to avoid overlaps, delays, and collisions between trains. The temporal uncertainties and constraints that may arise on the railway network may degrade the planned schedules and consequently affect the availability of the transportation system. This leads to many problems in the decision and optimization of the railway transport systems. In this context, we propose a new fuzzy stochastic Petri nets for monitoring (SFPNM). The main goal of the proposed supervision approach is to allow an early detection of traffic disturbance to avoid catastrophic scenarios and preserve stability and security of the studied railway networks. Finally, to demonstrate the effectiveness and accuracy of the approach, an application to the case study of the Tunisian railway network is outlined. |
url |
http://dx.doi.org/10.1155/2021/5595065 |
work_keys_str_mv |
AT anismhala amonitoringapproachbasedonfuzzystochasticptimedpetrinetsofarailwaytransportnetwork AT anismhala monitoringapproachbasedonfuzzystochasticptimedpetrinetsofarailwaytransportnetwork |
_version_ |
1721453706353836032 |