PROCEEDINGS IPMU '08
Aggregation Selection for Hierarchical Fuzzy Signatures: A Comparison of Hierarchical OWA and WRAO
S. Mendis, T. Gedeon.
In general, intelligent decision making
systems receive information
that is very sparse and which is
likely to be hierarchically correlated.
Our previous research has
show that hierarchical Fuzzy Signatures
are effective, efficient, robust
and flexible with such inputs.
Earlier, we introduced the generalised
Weighted Relevance Aggregation
Operator (WRAO) for hierarchical
Fuzzy Signatures. In this paper,
we compare the generalised Ordered
Weighted Averaging (GOWA)
operator with WRAO to select the
best aggregation method for hierarchical
Fuzzy Signatures. Additionally,
we show a method of learning
hierarchical GOWA using the
Levenberg-Marquardt optimization
Method.
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