Using fuzzy places and hypertokens to reduce the number of states in stochastic Petri nets

被引：0
|
作者：
de Korvin, A
Kleyle, R [1 ]
机构：
[1] Indiana Univ Purdue Univ, Dept Math Sci, Indianapolis, IN 46202 USA
[2] Univ Houston, Dept Math & Comp Sci, Houston, TX 77002 USA
来源：
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2000年 / 9卷 / 1-2期
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A difficulty often encountered when using the Petri net approach to stochastic modeling is a proliferation in the number of states in the associated Markov chain. In this paper we present a solution to this proliferation problem by introducing the concept of a fuzzy stochastic Petri net. This paper then focuses on the problem of finding the stationary probability of reaching some selected output nodes, starting from selected input nodes when using a fuzzy set approach to modeling with stochastic Petri nets.
引用
收藏
页码：43 / 51
页数：9
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