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Two-phase Incremental Clustering Algorithm Based on Immune Response and Ant Colony

机译:基于免疫反应和蚁群的两阶段增量聚类算法

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It is a trend for paradigms of nature-inspired computing to hybrid. Inspired by the principle of immune response in the immune system, a novel incremental data clustering algorithm called IRA was proposed in previous work. It obtains high quality clustering. However, the number of clusters obtained by IRA is more than the actual ones. Therefore, the clustering algorithm based on ant colony called OAA is taken into account to optimize the results of IRA. Then, both IRA and OAA form a two-phase incremental clustering algorithm. The experimental results are presented and discussed which demonstrate acceptable accuracy couple with efficiency in running time and compression.
机译:对于自然启发式的计算范式来说,这是一种趋势。受免疫系统中免疫反应原理的启发,先前的工作中提出了一种新的增量数据聚类算法,称为IRA。它获得高质量的聚类。但是,IRA获得的群集数量比实际的要多。因此,考虑了基于蚁群的聚类算法OAA,以优化IRA的结果。然后,IRA和OAA都形成了两阶段增量聚类算法。提出并讨论了实验结果,这些结果证明了可接受的精度以及运行时间和压缩效率。

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