Because of the existence of Dimension effect and the data sparseness problem in high dimensional data
, most of the existing clustering algorithm is in a state of failure at present.
The impact of the dimension and the number of data points is considered separately for low dimensional data
spaces (Sections 3-4) and for high dimensional data
spaces (Section 5).
However, no existed works consider how to process similarity search on high dimensional data
stream, which is often used in many applications.
The days of companies having several different software packages to gather and analyze dimensional data
are coming to a close.
also is provided for railcars, ships, aircraft and containers.
Driving the change is the move to fully integrate measurement and inspection into the manufacturing process so dimensional data
can be used to correct or modify operations, preventing the production of non-conforming parts.
Because the products are so parametrical dimensional and run in many sizes, the possibility for human error in entering dimensional data
They must be placed as close as practical to the process itself, if not within it, while maintaining the capability to accurately gather large amounts of dimensional data