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计算机工程 ›› 2010, Vol. 36 ›› Issue (18): 35-37. doi: 10.3969/j.issn.1000-3428.2010.18.013

• 软件技术与数据库 • 上一篇    下一篇

改进的基于密度方法的态势聚类显示算法

赵恩来,郝文宁,赵水宁,韩宪勇   

  1. (解放军理工大学工程兵工程学院,南京 210007)
  • 出版日期:2010-09-20 发布日期:2010-09-30
  • 作者简介:赵恩来(1985-),男,硕士研究生,主研方向:聚类分析,时间序列数据挖掘;郝文宁,副教授、博士;赵水宁,讲师、博士;韩宪勇,助教、硕士

Improved Situation Clustering Display Algorithm Based on Density Method

ZHAO En-lai, HAO Wen-ning, ZHAO Shui-ning, HAN Xian-yong   

  1. (Engineering Institute of Corps of Engineers, PAL University of Science & Technology, Nanjing 210007, China)
  • Online:2010-09-20 Published:2010-09-30

摘要:

为解决计算机标图过程中因缩小地图比例尺而导致的标号扎堆问题,通过分析邻域参数,利用DBSCAN算法寻找相互遮挡的标号,在其质心处用标图代替扎堆标号。针对DBSCAN算法的不足,结合实际应用情况,将传统基于密度方法的圆形邻域改为针对应用的多边形邻域,提出改进的算法BDIRCAN。实验结果表明,BDIRCAN算法能较好地解决标号扎堆问题,避免对临近但不相互遮挡的标号进行错误的聚类。

关键词: DBSCAN算法, 引射线法, 聚类, 标图, 标号

Abstract:

In order to solve the problem that close military symbols may shelter each other while reducing scale of map in computer plotting, by analyzing the parameters of neighborhood, this paper uses Density-Based Spatial Clustering of Applications with Noise(DBSCAN) algorithm to seek the symbols sheltering each other, and uses plot instead of symbols in their centroid. Aiming at the shortcomings of DBSCAN algorithm, it proposes an improved algorithm named Based on Density and Irregular Region Clustering of Applications with Noise(BDIRCAN), which considers application conditions and changes the traditional circular neighborhood to the applied irregular polygonal neighborhood. Experimental result shows that BDIRCAN can solve the problem well and avoid clustering the symbols which stay near but do not shelter each other.

Key words: Density-Based Spatial Clustering of Applications with Noise(DBSCAN) algorithm, radial algorithm, clustering, plot, symbol

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