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...

Full description

Bibliographic Details
Main Author: Anis M’hala
Format: Article
Language:English
Published: Hindawi-Wiley 2021-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2021/5595065
id doaj-557817e5f56e4d3fb174fcab6c380813
record_format Article
spelling 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