刘启亮, 李光强, 邓敏. 一种基于局部分布的空间聚类算法[J]. 武汉大学学报 ( 信息科学版), 2010, 35(3): 373-377.
引用本文: 刘启亮, 李光强, 邓敏. 一种基于局部分布的空间聚类算法[J]. 武汉大学学报 ( 信息科学版), 2010, 35(3): 373-377.
LIU Qiliang, LI Guangqiang, DENG Min. A Local Distribution Based Spatial Clustering Algorithm[J]. Geomatics and Information Science of Wuhan University, 2010, 35(3): 373-377.
Citation: LIU Qiliang, LI Guangqiang, DENG Min. A Local Distribution Based Spatial Clustering Algorithm[J]. Geomatics and Information Science of Wuhan University, 2010, 35(3): 373-377.

一种基于局部分布的空间聚类算法

A Local Distribution Based Spatial Clustering Algorithm

  • 摘要: 设计了一种度量邻近域内空间实体局部分布的新指标——中值角度,在此基础上,提出了一种基于空间实体局部分布的空间聚类算法。该方法递归搜索空间实体集中所有局部分布度量值相近且非离群的点,并将其聚为一类。通过模拟数据和实际数据进行实验发现,所提出的算法比DBSCAN算法的聚类结果更合理,具有很好的抗噪性,能发现任意形状的聚类。

     

    Abstract: All existing spatial clustering methods only utilize the spatial distances and the numbers of entities in the spatial nearest neighborhood to find the spatial clusters in the spatial database,without taking the spatial local distribution characters into account.Hence,the clustered results are unreasonable in many cases.To overcome such limitations,we propose a new spatial clustering algorithm based upon the local distribution among the entities in certain spatial neighborhood,where median angle for each entity is employed to measure its property of local distribution.In the process of spatial clustering,a series of recursive search were implemented for all the entities so that those entities with its median angle being very similar are clustered.Two tests were implemented to demonstrate that the proposed method is more prominent than DBSCAN,and can be used to find the clusters with arbitrary shapes.

     

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