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    基于信任知识库的概率模糊认知图

    Probabilistic Fuzzy Cognitive Map Based on Belief Knowledge Database

    • 摘要: 模糊认知图较难表示概念间因果关系测度的不确定性、因果联系的时空特性及专家对知识的不确定性 在继承模糊认知图模型优点的前提下 ,在概念间的因果关系中引入条件概率及信任知识库表示 ,提出基于信任知识库的概率模糊认知图模型 该模型用条件概率及信任知识库表示因果联系的时空特性、专家对知识及概念间因果关系测度的不确定性 ,从而将因果关系测度的不确定性、因果联系的时空特性及专家对知识的不确定性有效地融入模糊认知图中 ,自然扩展了模糊认知图模拟因果关系的能力 ,较大限度地减少了认知图对现实世界模拟的失真 最后通过实验说明了基于信任知识库的概率模糊认知图模型 ,具有比FCM更强的模拟能力

       

      Abstract: Fuzzy cognitive map (FCM) fails to represent the measures of uncertain causal relationships, spatial and temporal characteristic in causal relationships, and the uncertainty of expert’s knowledge Conditional probability and belief knowledge database are introduced to solve those problems, and belief knowledge database based probabilistic fuzzy cognitive map (BKPFCM) is presented In BKPFCM, the conditional probability and belief knowledge database express the measures of uncertain causal relationships and expert’s knowledge with uncertainty, so, the simulating capability of FCM is extended naturally Finally, experiments show that BKPFCM is more flexible and robust than FCM

       

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