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

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

CLC Number: 

• TP301.6