...
首页> 外文期刊>Scientific Research and Essays >Clustering analysis of the districts in Erzurum for traffic accidents between 2002 and 2007
【24h】

Clustering analysis of the districts in Erzurum for traffic accidents between 2002 and 2007

机译:2002年至2007年Erzurum地区交通事故区域的聚类分析

获取原文

摘要

In this study, clustering analysis was done by using date of road traffic accidents (RTAs) in districts of Erzurum in Turkey occurring at 2002 to 2007 years. Province of Erzurum has eighteen districts. Road surface situation, solstice, vehicle type and number of RTAs are used in clustering analysis. Clustering analysis was done by using both traditional k-means and fuzzy c-means techniques. Districts are divided five cluster by clustering analysis are done according to two techniques. Also five risk levels were identified by center values of clusters. Risk levels of districts were demonstrated in thematic maps. The thematic maps were constituted by using geographical information systems (GIS). The thematic maps demonstrated members of cluster that districts are separated by clustering analysis according to both traditional k-means and fuzzy c-means techniques. Results obtained from this study were compared. It was observed that fuzzy c-means technique gives accurate and consistent results at least k-means technique. Also, It was determined that GIS is advantageous to show and understand the results on the thematic maps.
机译:在这项研究中,采用土耳其Erzurum地区发生在2002年至2007年之间的道路交通事故(RTA)日期进行了聚类分析。埃尔祖鲁姆省有十八个区。聚类分析中使用了路面状况,至多,车辆类型和RTA数量。通过使用传统的k均值和模糊c均值技术进行聚类分析。根据两种技术,通过聚类分析将区域划分为五个聚类。还通过聚类的中心值确定了五个风险级别。专题图显示了地区的风险水平。专题图是使用地理信息系统(GIS)绘制的。专题图展示了根据传统k均值和模糊c均值技术通过聚类分析将区分开的聚类成员。比较了从这项研究中获得的结果。观察到,模糊c均值技术至少可以给出k均值技术的准确一致的结果。此外,已确定GIS有利于在主题地图上显示和理解结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号