CAJ | 학술논문

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。
공간취류시공간수거알굴중적일충중요수단,채용공간취류기술진행유용신식적획취구유중요적현실의의。침대성시수도실시로황적특점,재상견적성시수도실시교통사건검측수거알굴-관련규칙산법적정황하,파여성시수도상관적대상간작실시로황적속성,계산성시수도간적신식적,근거신식적적변화실현성시수도실시로황적취류,제출료기우신식적적성시수도실시교통사건검측취류산법( Entropy-based City Tunnel Real-time,ECRT)。실험표명,통과기재실제수거집상진행적측시,산법ECRT고효지해결료탁복관계적복잡공간수거집중대상적취류문제。
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.