Abstract: This paper analyzes the features of the spatial data and difficulties and shortages of traditional methods in clustering analysis of spatial data. A novel spatial data clustering method based on improved evolutionary algorithm, called SDCEA is proposed. It effectively solves the main problems in clustering analysis of spatial data and enhances the flexibility and efficiency of the clustering analysis. Numerical experiments show that SDCEA has better performance.

Key words: spatial data, data mining, evolutionary algorithm, clustering

摘要： 分析空间数据的特点和用常规方法进行空间数据聚类分析的难点与不足，提出一种基于改进的演化算法空间数据聚类方法——SDCEA。解决用传统方法进行空间数据聚类分析时存在的问题，增强聚类分析方法的灵活性和有效性。实验结果表明，对于空间数据的聚类分析问题，该算法具有很好的性能。

关键词: 空间数据, 数据挖掘, 演化算法, 聚类

CLC Number: 

• TP311