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Ant colony optimization of clustering models

✍ Scribed by Thomas A. Runkler

Publisher
John Wiley and Sons
Year
2005
Tongue
English
Weight
319 KB
Volume
20
Category
Article
ISSN
0884-8173

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✦ Synopsis

The original ant system algorithm is simplified leading to a generalized ant colony optimization algorithm that can be used to solve a wide variety of discrete optimization problems. It is shown how objective function based clustering models such as hard and fuzzy c-means can be optimized using particular extensions of this simplified ant optimization algorithm. Experiments with artificial and real datasets show that ant clustering produces better results than alternating optimization because it is less sensitive to local extrema.

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