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We use centroid proximity measure for clustering customers.
The proximity measure is used to guide the discussion phase of consensus reaching process.
Each proximity measure is evaluated with respect to its predictive performance.
An important element on the centroid proximity measure is the centroid or gravity center of groups.
Graphical and analytical representation of this proximity measure is shown in Fig 5.
It uses on-line clustering of the input output data with a recursively calculated spatial proximity measure.
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Until now, the closest proximity measured data available for local solar resource measurement and prediction was in Lake Charles, LA, about 100 miles to the west.
The following lemma gives a relation between two proximity measures.
New search directions and proximity measures are defined by these kernel functions.
We build upon this work by integrating proximity measures into the Γ of the TERGM.
Figure4 provides illustration of the sub-graph configurations that constitute 4 of the proximity measures.
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