计算机工程 ›› 2012, Vol. 38 ›› Issue (18): 158-161.doi: 10.3969/j.issn.1000-3428.2012.18.043

• 人工智能及识别技术 • 上一篇    下一篇

基于多主体技术和数学形态学的空间聚类算法

路 红1,陈立潮1,潘理虎1,2,闫慧敏2,黄河清2   

  1. (1. 太原科技大学计算机科学与技术学院,太原 030024;2. 中国科学院地理科学与资源研究所,北京 100101)
  • 收稿日期:2011-11-09 修回日期:2012-01-04 出版日期:2012-09-20 发布日期:2012-09-18
  • 作者简介:路 红(1975-),女,硕士研究生,主研方向:数据挖掘,人工智能;陈立潮,教授、博士;潘理虎,副教授、博士;闫慧敏,副研究员、博士;黄河清,研究员、博士
  • 基金项目:
    国家自然科学基金资助项目(41071344);太原科技大学博士创新基金资助项目(20102030)

Spatial Clustering Algorithm Based on Multi-agent Technology and Mathematic Morphology

LU Hong1, CHEN Li-chao1, PAN Li-hu1,2, YAN Hui-min2, HUANG He-qing2   

  1. (1. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, China; 2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)
  • Received:2011-11-09 Revised:2012-01-04 Online:2012-09-20 Published:2012-09-18

摘要: 空间数据复杂多变、数据量庞大,且数据分析较为困难。为解决该问题,提出一种基于多主体技术和数学形态学灰度形态运算的聚类算法。将结构元素作为智能个体,Agent根据其所处空间位置环境的Moore Neighborhood值或VN Neighborhood值,采用OCC算子自主选择做灰度膨胀或腐蚀运算。实验结果表明,该算法具有较好的准确性、可靠性和灵活性,能对任意聚类形状进行快速聚类。

关键词: Agent技术, 数学形态学, 灰度膨胀, 结构元素, 灰度腐蚀, 空间聚类算法

Abstract: The spatial data is complex, changeful, and mass, so the work of spatial data analysis is onerous, a spatial clustering algorithm based on multi-agent technology and mathematic morphology is proposed to solve this problem. The structural element of the mathematic morphology is selected as Agent. Based on the values of Moore Neighborhood or VN Neighborhood in the environment of their spatial location, the Agents autonomously choose OCC operator to do gray dilation or erosion operation to implement spatial clustering. Experimental results show that this algorithm has significant accuracy, reliability, flexibility, and can rapidly cluster any shapes of clustering.

Key words: Agent technology, mathematic morphology, gray dilation, structure element, gray erosion, spatial clustering algorithm

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