Characterizing Features
Two features have been used to characterize the OWA operators. The first is the attudinal character(orness).
This is defined as
It is known that .
In addition A − C(max) = 1, A − C(ave) = A − C(med) = 0.5 and A − C(min) = 0. Thus the A − C goes from 1 to 0 as we go from Max to Min aggregation. The attitudinal character characterizes the similarity of aggregation to OR operation(OR is defined as the Max).
The second feature is the dispersion. This defined as
An alternative definition is The dispersion characterizes how uniformly the arguments are being used
Read more about this topic: Ordered Weighted Averaging (OWA) Aggregation Operators
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