Abstract:
A simplified clustering algorithm that enables on-line
partitioning of data streams is proposed. The algorithm applies
adaptive-distance metric to identify clusters with different shape and
orientation. It is applicable to a wide range of practical evolving system
type applications as diagnostics and prognostics, system identification,
real time classification, and process quality monitoring and control.