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The Architecture of Ant-Based Clustering to Improve Topographic Mapping

机译:基于蚁群的聚类体系结构以改善地形图

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摘要

This paper analyzes the popular ant-based clustering approach of Lumer/Faieta. Analysis of formulae unveils that ant-based clustering is strongly related to Kohonen's Self-Organizing Batch Map. Known phenomena, e.g. formation of too many and too small clusters, can be explained due to that. Furthermore it is shown how topographic mapping of ant-based methods is substantially improved by means of a modified error function. This is demonstrated on few selected fundamental clustering problems.
机译:本文分析了Lumer / Faieta流行的基于蚂蚁的聚类方法。公式分析显示,基于蚂蚁的聚类与Kohonen的自组织批处理图密切相关。已知现象,例如因此,可以解释太多和太小的簇的形成。此外,还显示了如何通过修改的误差函数显着改善基于蚂蚁的方法的地形图绘制。这在一些选定的基本聚类问题上得到了证明。

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