应用带标识的模糊Petri网的知识表示方法  

Method of knowledge representation based on marked fuzzy Petri net

作　　者：孙晓玲[1] 王宁[1] 

机构地区：[1]合肥师范学院数学系,合肥230061

出　　处：《计算机工程与应用》2010年第6期48-51,55,共5页Computer Engineering and Applications

基　　金：安徽省自然科学基金(No.KJ2008B109ZC);安徽省高校青年教师资助计划项目基金(No.2008JQW1124);安徽省高等学校省级自然科学研究项目(No.KJ2009B148Z);高等学校优秀青年人才基金项目(No.2009SQRZ157)~~

摘　　要：提出一种在某些库所中带有标识的模糊Petri网模型来进行知识表示。为了获得更多的加权模糊产生式规则的信息,在知识表示的过程中考虑了权值,确定性因子,阈值等参数。这种模糊Petri网充分利用了Petri网的并行处理能力。随着带标识的模糊Petri网的运行,网中标识的变化可以标记加权模糊推理的运行。通过文中给出的基于相似性测度的计算方法可以更加高效地计算出多层加权模糊推理的推理结果。A marked fuzzy Petri net with some places containing tokens is proposed to represent knowledge.To gain more information of weighted fuzzy production rules,the knowledge parameters such as weight,certainty factor,threshold value etc.are taken into account in the course of knowledge representation.The fuzzy Petri net take use of parallel processing ability of Petri net fully.With the processing of marked fuzzy Petri net,the change of the token in the net can mark the process of the weighted fuzzy reasoning.According to the computing method based on the similarity measure,the deduced consequence of the multilevel weighted fuzzy reasoning can be computed more efficiently.

关 键 词：带标识的模糊Petri网 加权模糊推理 知识表示 

分 类 号：TP273.4[自动化与计算机技术—检测技术与自动化装置]