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Simulation Symposium, Annual (2005)
San Diego, California, USA
Apr. 4, 2005 to Apr. 6, 2005
ISSN: 1080-241X
ISBN: 0-7695-2322-6
pp: 99-106
Graham Horton , Otto-von-Guericke Universit?t Magdeburg
Claudia Isensee , Otto-von-Guericke Universit?t Magdeburg
<p>The analysis of discrete stochastic models such as generally distributed stochastic Petri nets can be done using state space-based methods. The behavior of the model is described by a Markov chain that can be solved mathematically. The phase-type distributions that are used to describe non-Markovian distributions have to be approximated. An approach for the fast and accurate approximation of discrete phase-type distributions is presented. This can be a step towards a practical state space-based simulation method, whereas formerly this approach often had to be discarded as unfeasible due to high memory and runtime costs.</p> <p>Discrete phases also fit in well with current research on proxel-based simulation. They can represent infinite support distribution functions with considerably fewer Markov chain states than proxels. Our hope is that such a combination of both approacheswill lead to a competitive simulation algorithm.</p>
Graham Horton, Claudia Isensee, "Approximation of Discrete Phase-Type Distributions", Simulation Symposium, Annual, vol. 00, no. , pp. 99-106, 2005, doi:10.1109/ANSS.2005.12
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