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An Improved Ant-Colony Clustering Algorithm Based on the Innovational Distance Calculation Formula

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.