基于直觉模糊Petri网的加权直觉模糊推理  

Weighted intuitionistic fuzzy reasoning based on intuitionistic fuzzy Petri nets

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230601

出　　处：《计算机工程与应用》2013年第4期50-53,94,共5页Computer Engineering and Applications

基　　金：安徽省省级自然科学研究项目(No.KJ2012Z322);安徽省高等学校优秀青年人才基金项目(No.2009SQRZ157)

摘　　要：利用直觉模糊集合较好地表现不确定信息的能力和Petri网的并行处理能力,构建了直觉模糊Petri网模型。给出了输入权值、变迁阈值等多种约束条件下的直觉模糊推理算法。该算法将直觉模糊推理过程转化为矩阵的运算过程可充分利用直觉模糊Petri网的并行推理能力,有效地避免同一变迁不必要地重复激发从而节省推理时间。实例分析表明所给出的直觉模糊推理算法较已有算法更加合理并且高效。Intuitionistic fuzzy Petri net model is constructed using intuitionistic fuzzy sets＇ better performance of uncertain information and parallel processing capability of Petri network. The input weights, threshold of transition under multiple con- straints for intuitionistic fuzzy reasoning algorithm is given. The algorithm takes the intuitionistic fuzzy reasoning process into matrix multiplication process can make full use of intuitionistic fuzzy Petri net parallel reasoning ability, effectively avoid the same transition unnecessary repetitive excitation so as to save the inference time. The last example analysis shows that the intu- itionistic fuzzy reasoning algorithm is better than the existing algorithm and more reasonable and efficient.

关 键 词：直觉模糊集合 直觉模糊Petri网 直觉模糊逻辑 模糊推理 直觉模糊产生式规则 

分 类 号：TP182[自动化与计算机技术—控制理论与控制工程]