A hybrid fuzzy cognitive model based on weighted OWA operators and single-antecedent rules

作者：Lv Zhenbang^*; Zhou Lihua

来源：International Journal of Intelligent Systems, 2007, 22(11): 1189-1196.

DOI：10.1002/int.20243

Conventional fuzzy cognitive maps (FCMs) can only represent monotonic or symmetric causal relationships and cannot simulate the AND/OR combinations of the antecedent nodes. The rulebased fuzzy cognitive maps (RBFCMs) usually suffer from the well-known combinatorial rule explosion problem. A hybrid fuzzy cognitive model based on weighted OWA operators and single antecedent rules is proposed to eliminate the drawbacks of the existing FCM models. Hybrid fuzzy cognitive maps (HFCMs) represent the causal relationships with single-antecedent fuzzy rules and handle the various AND/OR relationships among the antecedent nodes with weighted OWA aggregation operators. Compared with conventional FCMs, HFCMs have more powerful cognitive capability. Compared with RBFCMs, HFCMs reduce the scale and complexity of the rule bases significantly and have better representation and inference performance.

• 出版日期2007-11
• 单位西安电子科技大学