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复杂系统可靠性估计的模糊神经Petri网方法
引用本文:原菊梅,侯朝桢,王小艺,吴勤.复杂系统可靠性估计的模糊神经Petri网方法[J].控制理论与应用,2006,23(5):687-691.
作者姓名:原菊梅  侯朝桢  王小艺  吴勤
作者单位:1. 中北大学分校,山西,太原,030008
2. 北京理工大学,信息科学技术学院,北京,100081
基金项目:国防基础研究基金资助项目.
摘    要:针对复杂系统可靠性建模难问题,提出了一种新的适用于复杂系统可靠性估计的模糊神经Petri网(简称为FNPN).文中首先给出了模糊神经Petri网的定义及其引发规则,然后给出了一种学习算法.该FNPN结合了模糊Petri网和神经网络各自的优点,既可以表示和处理模糊产生式规则的知识库系统又具有学习能力,可通过对样本数据学习调整模型中的参数以获得系统内部的等效结构,从而计算出非样本数据的系统的可靠度.最后以一无向网络为例说明该方法是可行的.

关 键 词:模糊神经Petri网  复杂系统  可靠性估计
文章编号:1000-8152(2006)05-0687-05
收稿时间:2005-04-27
修稿时间:2005-04-272005-11-08

Fuzzy neural Petri-net method for reliability estimation of complex systems
YUAN Ju-mei,HOU Chao-zhen,WANG Xiao-yi,WU Qin.Fuzzy neural Petri-net method for reliability estimation of complex systems[J].Control Theory & Applications,2006,23(5):687-691.
Authors:YUAN Ju-mei  HOU Chao-zhen  WANG Xiao-yi  WU Qin
Affiliation:College of North China Institute of Technology, Taiyuan Shanxi 030008, China; School of Information Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Abstract:A Fuzzy neural Petri-net method (FNPN) for estimating the reliability of complex systems is proposed. The definition and fire-rules of this FNPN are presented. A learning algorithm is put forward. This FNPN combines the advantages of fuzzy Petri-net and neural network. It can express and process the knowledge-based system of fuzzy productive rules, and posseses the capability of learning. The structure and parameters of the system can be determined by learning the sample data. An example of non-directional network is used to demonstrate the feasibility of this method.
Keywords:fuzzy neural Petri net  complex system  reliability estimate
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