Abstract
Various clustering methods based on the behavior of real ants have been proposed. In this paper, we develop a new algorithm in which the behavior of the artificial ants is governed by fuzzy IF–THEN rules. Our algorithm is conceptually simple, robust and easy to use due to observed dataset independence of the parameter values involved. In the experiment, spatial data source is come from the actual survey data in mine. LF algorithm and the fuzzy ant based spatial clustering algorithm separately to cluster these data. Through analysis and comparison the experimental results to prove that the fuzzy ant based spatial clustering algorithm enhances the clustering effect.
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Chen, Y., Han, M., Zhu, H. (2010). Ant Spatial Clustering Based on Fuzzy IF–THEN Rule. In: Cao, By., Wang, Gj., Guo, Sz., Chen, Sl. (eds) Fuzzy Information and Engineering 2010. Advances in Intelligent and Soft Computing, vol 78. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14880-4_62
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DOI: https://doi.org/10.1007/978-3-642-14880-4_62
Publisher Name: Springer, Berlin, Heidelberg
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