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。
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.
出处
《计算机工程》
CAS
CSCD
2012年第18期158-161,共4页
Computer Engineering
基金
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)
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
Agent technology; mathematic morphology; gray dilation; structure element; gray erosion; spatial clustering algorithm