基于多次灰色聚类的服务区定位方法及其应用

A Localization Method of Service Station Based on Repeated Grey Clustering and Its Application

为客观准确地评价高速公路服务区的重要度和贡献度,现提出采用多次灰色聚类方法定位服务区。将同一高速沿线的服务区作为聚类对象集,评价服务区的代表因子,如服务区的占地面积、驶入交通量及加油机台数等作为聚类因子集,计算各聚类界限及各因子在各类中所占权重,便可求得各聚类对象对各聚类标准的聚类系数,将聚类系数大小作为参数对服务区进行聚类排序分析。对于一次聚类运算结果中包含对象较多的类别,再以这一类服务区作为聚类对象集,重复运用灰色聚类,对服务区进行聚类排序分析。与常规灰色聚类法相比,多次聚类方法聚类层类别更多,定位更精准,能同时实现服务区的聚类及排序。

In order to give an objective and exact evaluation on the contribution and importance of expressway service station,repeated Grey clustering method is proposed.The service station along each expressway is applied as the clustering object set,while the site area,back-in traffic and number of units tanker are used as clustering index set.By calculating the limits and weights of index in each class,the clustering index of objects under corresponding clustering standard can be obtained,thus a sorting and clustering analysis process can be advanced by the clustering indexes.For the classes including too much objects,the same process can be applied to these classes.Comparing to normal Grey clustering method,the repeated Grey clustering method possess the advantage of more clustering layers,higher locating accuracy,and it can simultaneously accomplish the clustering and sorting of service station.