论文部分内容阅读
现有模糊认知图(Fuzzy Congnitive Map,FCM)模型忽略了原因节点间与或组合关系的不确定性.针对这一缺陷,作者通过引入加权的有序加权平均(Weighted Ordered Weighted Averaging,WOWA)算子来模拟原因节点间确定的或模糊的与或关系,提出了基于WOWA集结算子的模糊认知图框架.为增强传统FCM的因果认知性能,作者在此新的框架下,利用单前件模糊规则拓展数值型FCM的因果模糊测度,提出了一种混合模糊认知图模型.
The existing Fuzzy Congnitive Map (FCM) model ignores the uncertainty of the relationship between nodes and / or combinations.According to this flaw, the author introduced Weighted Ordered Weighted Averaging (WOWA) Operator to simulate the deterministic or ambiguous relation between nodes, a fuzzy cognitive graph framework based on WOWA assemble operator is proposed.In order to enhance the causal cognitive performance of traditional FCM, the author, under the new framework, The former fuzzy rule extends the causal fuzzy measure of numerical FCM, and proposes a hybrid fuzzy cognitive graph model.