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Schematic diagram of two consecutive queuing systems systems are represented by PB 1 (x 1 (t)), PB 2 (x 2 (t)), PE 1 (x 1 (t)), PE 2 (x 2 (t)), µ 1 (x 1 (t)), and µ 2 (x 2 (t)), respectively. The current arrival rate λ 1 (t) and input flow rate f in 1 (t) of the first system can be calculated using Eq. 10 and Eq. 11. The output flow rate f out 1 (t) depends not only on its own idle probability but also the blocking probability of the downstream system as described by Eq. 12. This is known as the congestion propagation phenomenon, where customers in the upstream system have to queue if the downstream system is blocked.

Schematic diagram of two consecutive queuing systems systems are represented by PB 1 (x 1 (t)), PB 2 (x 2 (t)), PE 1 (x 1 (t)), PE 2 (x 2 (t)), µ 1 (x 1 (t)), and µ 2 (x 2 (t)), respectively. The current arrival rate λ 1 (t) and input flow rate f in 1 (t) of the first system can be calculated using Eq. 10 and Eq. 11. The output flow rate f out 1 (t) depends not only on its own idle probability but also the blocking probability of the downstream system as described by Eq. 12. This is known as the congestion propagation phenomenon, where customers in the upstream system have to queue if the downstream system is blocked.

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Abstract: The COVID-19 pandemic has affected communities worldwide. The metro system, an essential means of public transportation in many cities, is particularly vulnerable to the spread of the virus due to its limited space and complex passenger flow structure. As the basis of quick and effective management decision-making, it is very important bu...

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Context 1
... consider two consecutive M t /G(x)/C/C queuing systems, the states of which can be represented by x 1 (t) and x 2 (t), as depicted in Fig. 4. The blocking probabilities, idle probabilities, and service rates of the first and second í µí²™ í µí¿ (í µí²•) í µí²™ í µí¿ (í µí²•) í µí²‡í µí²Ší µí² í µí¿ í µí²• í µí²‡í µí²í µí²–í µí²• í µí¿ í µí²• = í µí²‡í µí²Ší µí² í µí¿ í µí²• í µí²‡í µí²í µí²–í µí²• í µí¿ í µí²• ...
Context 2
... each passenger is a regular hexagon, we can convert the allowed density to the allowed social distance. By gradually increasing the allowed density in halls and platforms from 0.25 to 5 per/m 2 (namely, gradually decreasing the social distance from 2.15 m to 0.48 m), we observe changes in TNNET using the QEM approach. The results are shown in the Fig. 24. In consideration of the potential of outside station infection, both measures of social distancing and allowed entering proportion control achieve similar results with a trade-off between inside and outside contagion. Observations of TNNET with low travel demand show a decrease in TNNET as allowed density decreases until it reaches ...

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