空间聚类是空间数据挖掘中的一种重要手段,采用空间聚类技术进行有用信息的获取具有重要的现实意义。针对城市隧道实时路况的特点,在常见的城市隧道实时交通事件检测数据挖掘-关联规则算法的情况下,把与城市隧道相关的对象看作实时路况的属性,计算城市隧道间的信息熵,根据信息熵的变化实现城市隧道实时路况的聚类,提出了基于信息熵的城市隧道实时交通事件检测聚类算法( Entropy-based City Tunnel Real-time,ECRT)。实验表明,通过其在实际数据集上进行的测试,算法ECRT高效地解决了拓扑关系的复杂空间数据集中对象的聚类问题。%Spatial clustering is an important tool in spatial data mining,spatial clustering technology accessing useful information has im-portant practical significance. In view of city tunnel real-time traffic characteristics in common urban tunnel real-time traffic incident de-tection data mining - the case of the association rules algorithm,the city tunnel object as properties of the real-time traffic,calculate the entropy of information between the city tunnel,achieve real-time city tunnel traffic clustering based on entropy changes,the ECRT ( en-tropy-based city tunnel real-time) algorithm is proposed. The experiments show algorithm ECRT used in the actual data set test can ef-fectively resolve the problem of object clustering in complex spatial data set of topology relation.
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