Poisson Simulation—A Method For Generating Stochastic Variations In Continuous System Simulation  

Oleh:

Gustafsson, Leif

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Simulation vol. 74 no. 5 (Apr. 1998), page 264-274.
Topik: CSS; differential equations; Poisson distribution; Poisson process; random; stochastic process
Fulltext: 264.pdf (990.22KB)

Isi artikel

In continuous systems simulation a model is built as a system of differential equations. An implicit assumption is that the number of items is so large that the changes can then be regarded as continuous. However, many systems can be modeled by differential equations when the numbers involved are moderately large. Such systems show stochastic variations that can be described in terms of events per time unit. If the events happen one at a time, and if the number of events during the interval is independent of both the number of past events and the times these events occurred, we have a Poisson process. The system’s variations can be modeled by replacing the flow to or from a state during the integration step with a Poisson probability. This not only adds variations to the model, but can also reveal system properties not covered by continuous system simulation. Furthermore, the "intensity parameter" controlling the flow may vary over time without further problems.

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