Fuzzy Ant Based Spatial Clustering
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 set. Firstly, we define the average distance between objects, and the average distance is the domain of the object similarity. Secondly, the similarity between objects is mapped a domain of fuzzy sets by membership function. Finally, by the given confidence level, fuzzy sets will be separated into universal set. The universal set will decide that ants pick up or put down the object, in the experiment, spatial data source comes 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.
fuzzy set ant colony spatial clustering
CHEN Ying-xian
College of Resource and Environment Engineering, Liaoning Technical University Fuxin, China
国际会议
厦门
英文
224-227
2010-10-29（万方平台首次上网日期，不代表论文的发表时间）