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Proceedings Paper

Quantitative fuzzy cognitive maps for data integration
Author(s): Karl Perusich
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Paper 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.

Paper Details

Date Published: 9 May 2006
PDF: 9 pages
Proc. SPIE 6229, Intelligent Computing: Theory and Applications IV, 622905 (9 May 2006); doi: 10.1117/12.666569
Show Author Affiliations
Karl Perusich, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 6229:
Intelligent Computing: Theory and Applications IV
Kevin L. Priddy; Emre Ertin, Editor(s)

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