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Identification of Railway Transport Systems using stochastic P-timed Petri nets model

机译:基于随机P-时间Petri网模型的铁路运输系统识别

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The Railway transportation networks can be considered as discrete event systems with time constraints. The time factor is a critical parameter, since it includes dates and schedules to be respected in order to avoid overlaps, delays and collisions between trains. Petri nets have been recognized as powerful modelling and analysis tools for discrete event systems with time constraints. So, they are suitable for railway transportation systems. This article is devoted to the modelling and identification of the Tunisian Railway Network. The proposed approach consists in identifying, from experimental measurements, the dynamical behavior of the system by using interpreted Stochastic P-timed Petri Nets (SP-TPNs). The resulting model is suitable to simulate the traffic and also to evaluate the influence of different types of disturbances on the expected schedule.
机译:铁路运输网络可以看作是具有时间限制的离散事件系统。时间因素是一个关键参数,因为它包括要遵守的日期和时间表,以避免火车之间的重叠,延误和碰撞。 Petri网已被公认为具有时间限制的离散事件系统的强大建模和分析工具。因此,它们适用于铁路运输系统。本文致力于突尼斯铁路网络的建模和识别。所提出的方法包括通过使用解释的随机P定时Petri网(SP-TPN)从实验测量中识别系统的动力学行为。结果模型适合于模拟交通,还可以评估不同类型的干扰对预期时间表的影响。

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