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.