Abstract
This article applies the improved ant colony algorithm to the fuzzy c-means clustering, which overcomes sensitivity to initialization of fuzzy clustering method(FCM). This article improves the shortcomings which the traditional genetic algorithm and the ant colony algorithm work step-by-step, makes the mix algorithm work in the entire cluster’s process, simultaneously, puts the a swarm degree function in the ant colony algorithm, enhanced the ant algorithm search of the overall situation, increase the algorithm traversal the optimization capacity.
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Haifeng, Z. (2013). An Improved Ant Colony Algorithm Combined with Genetic Algorithm and Its Application in Image Segmentation. In: Du, Z. (eds) Intelligence Computation and Evolutionary Computation. Advances in Intelligent Systems and Computing, vol 180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31656-2_55
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DOI: https://doi.org/10.1007/978-3-642-31656-2_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31655-5
Online ISBN: 978-3-642-31656-2
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