DBSCAN是一种基于密度的空间聚类算法，在处理空间数据时具有快速、有效处理噪声点和发现任意形状的聚类等优点。
DBSCAN is a density based clustering algorithm that can efficiently discover clusters of arbitrary shape and can effectively handle noise.
实验结果表明，新算法较基于密度的带噪声数据应用的空间聚类方法(DBSCAN)具有更好的聚类性能。
Experimental results show that the new algorithm has better performance than Density Based Spatial Clustering of Applications with Noise (DBSCAN).
实验结果表明，新算法较基于密度的带噪声数据应用的空间聚类方法(DBSCAN)具有更好的聚类性能。
Experimental results show that the new algorithm has better performance than Density Based Spatial Clustering of Applications with Noise (DBSCAN).
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