邓敏, 彭东亮, 刘启亮, 石岩. 一种基于场论的层次空间聚类算法[J]. 武汉大学学报 ( 信息科学版), 2011, 36(7): 847-852.
引用本文: 邓敏, 彭东亮, 刘启亮, 石岩. 一种基于场论的层次空间聚类算法[J]. 武汉大学学报 ( 信息科学版), 2011, 36(7): 847-852.
DENG Min, PENG Dongliang, LIU Qiliang, SHI Yan. A Hierarchical Spatial Clustering Algorithm Based on Field Theory[J]. Geomatics and Information Science of Wuhan University, 2011, 36(7): 847-852.
Citation: DENG Min, PENG Dongliang, LIU Qiliang, SHI Yan. A Hierarchical Spatial Clustering Algorithm Based on Field Theory[J]. Geomatics and Information Science of Wuhan University, 2011, 36(7): 847-852.

一种基于场论的层次空间聚类算法

A Hierarchical Spatial Clustering Algorithm Based on Field Theory

  • 摘要: 从空间数据场的角度出发,提出了一种基于场论的层次空间聚类算法(简称HSCBFT)。该算法是通过模拟空间实体间的凝聚力来描述空间实体间的相互作用,进而采取层次凝聚的策略进行聚类。通过实验分析可以发现,层次空间聚类算法具有如下优势:①空间聚类簇中各空间实体很好地满足了空间邻近且专题属性相似的要求;②能发现任意形状的空间簇,且具有良好的抗噪性;③输入参数较少。

     

    Abstract: In this paper,a hierarchical spatial clustering algorithm based on field theory(HSCBFT in abbreviation) is proposed.The field theory of spatial data is firstly employed to describe the interaction among spatial entities.Then,the agglomerative strategy is utilized to find clusters at different levels.Two experiments are preformed to illustrate three advantages of our algorithm.i) It can commendably meet the requirement that clustered entities are close to each other and similar in thematic attribute;ii) It can also discovery clusters with arbitrary shape and is robust to outliers;iii) It needs to input fewer parameters.

     

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