Quantitative fuzzy cognitive maps for data integration

Karl Perusich

doi:10.1117/12.666569

9 May 2006 Quantitative fuzzy cognitive maps for data integration

Karl Perusich

Proceedings Volume 6229, Intelligent Computing: Theory and Applications IV; 622905 (2006) https://doi.org/10.1117/12.666569
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

Fuzzy cognitive maps are an emerging technique for knowledge elicitation and data synthesis. The technique can capture the cause and effect relationships that subject matter experts believe to exist about a problem. A chief advantage of this method is that a common metric for different attributes does not need to be determined because states of attributes are compared to states of attributes. This is also a disadvantage because the map can only infer a qualitative state for a node of interest, not a numerical value. To overcome this limitation, nodes are modeled using fuzzy sets that are then propagated through the map. Borrowing techniques used in fuzzy control systems, the scaled fuzzy sets can then be used to yield a crisp numerical value for the attribute represented by the node.

Citation Download Citation

Karl Perusich "Quantitative fuzzy cognitive maps for data integration", Proc. SPIE 6229, Intelligent Computing: Theory and Applications IV, 622905 (9 May 2006); https://doi.org/10.1117/12.666569

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