乘积型随机Petri网的算法——一种新方法

J. L. Coleman
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引用次数: 14

摘要

利用乘积型随机Petri网(sf - spn)中各利用率之间的一般关系,推导出一种计算归一化常数的方法。该方法将许多状态的贡献作为几何和收集在一起,通常提供了一种与初始标记大小无关的数值复杂性的递归算法。将该方法应用于一些简单的算例,得到了归一化常数的闭型解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithms for product-form stochastic Petri nets-A new approach
A general relationship between utilizations in product-form stochastic Petri nets (PF-SPNs) is used to derive a method for calculating the normalizing constant. The method collects the contributions of many states together as geometric sums and in general provides a recursive algorithm with numerical complexity independent of the size of the initial marking. The technique is applied to some simple examples, and closed-form solutions are obtained for the normalizing constant.<>
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