一种面向GIS系统的高维数据双层聚类方法

A two-level clustering algorithm for High-Dimensional data of GIS

在分析处理GIS系统数据的过程中,提出了一种对高维数据属性的双层聚类方法,该方法考虑了数据属性间的差异对聚类结果的影响,能够准确的发现两种性质的空间集簇。实验结果表明,该方法在发现空间对象的任意形状密集区域以及性质相同的若干类空间集簇上有很好的效果。

With analysing and processing the GIS data,we present a new clustering approach which can radically partition high-dimensional data.This proposed method have considered the differences between the data attributes impacting on the clustering results.Experimental results show that it can exactly divide the objects in geography space into some density-based regions and divide each of these regions into some sub-regions with representative center at the same time.