文件名称:An-Improved-Ant-Colony-Clustering-Algorithm-Based
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Focused on the disadvantage of classical Euclidian
distance in data clustering analysis, we propose an improved
distance calculation formula, which describes the local
compactness and global connectivity between data points.
Furthermore, we improve ant-colony clustering algorithm
by using the improved distance calculation formula.
Theoretical analysis and experiments show that this method
is more efficient and has the ability to identify complex nonconvex
clusters.
distance in data clustering analysis, we propose an improved
distance calculation formula, which describes the local
compactness and global connectivity between data points.
Furthermore, we improve ant-colony clustering algorithm
by using the improved distance calculation formula.
Theoretical analysis and experiments show that this method
is more efficient and has the ability to identify complex nonconvex
clusters.
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An Improved Ant-Colony Clustering Algorithm Based On The Innovational Distance Calculas Formula.pdf