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A differentiable macroscopic traffic model is also used.
The traffic model is applied after the earthquake for the most vulnerable areas in Montreal.
The traffic model is validated by numerical simulations of a mobile adaptive video streaming scenario.
An overall outlook for the nano-satellite industry and for a nano-satellite launch traffic model is given.
A traffic model is proposed for a metro single line with including both train traffic dynamic and passenger flow dynamic.
This analysis is the basis upon which the concept of multicast source prediction is proposed, and upon which a multicast traffic model is built.
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A highly-detailed traffic model was built in AIMSUN 8.1.2 model (Advanced Interactive Microscopic Simulator for Urban and Non-Urban Networks) for this case study to replicate and estimate traffic conditions and its related environmental and operational effects.
To overcome this, a dynamic modeling framework based on discrete-event simulation, which integrates environmental and traffic models, is explored in this paper.
Traffic modeling is very important in optimizing the network with efficient utilization of resources.
However, much of the current understanding of wireless traffic modeling is based on classical Poisson distributed traffic, which can yield misleading results and hence poor network planning.
Traffic modeling is a key in several network design issues, such as dimensioning of core and access network resources, developing pricing procedures, carrying out cost-revenue studies.
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