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

✍ Scribed by Zhenbang Lv; Lihua Zhou


Publisher
John Wiley and Sons
Year
2007
Tongue
English
Weight
132 KB
Volume
22
Category
Article
ISSN
0884-8173

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✦ Synopsis


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 singleantecedent 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.