基于改进动态聚类算法的公路客运枢纽节点优选

Optimizing Node of Passenger Station Based on Improved Dynamic Clustering Analysis

通过对原有聚类分析算法中向量贴近程度计算进行改进,计算各向量空间距离和角度贴近度,进而能够更精确地确定向量的综合贴近程度,以便于对向量进行聚类.结合公路客运枢纽节点优选特性,将改进后的聚类算法进行实例验证得到了较好的结果.该方法具有较强的实用性,对于公路客运枢纽的节点优选具有一定的实际意义.

In order to calculate the approach degree of vectors even more accurately, clustering algorithm on the original level is improved by calculating space distance and angle space similarity of the vector, and thus can more accurately determine the extent of the vector integrated close to the cluster of vectors. Preferred combination of characteristics of road passenger transport hub nodes, the improved clustering algorithm example shows good results obtained. The method is practical for the optimization of road passenger transport hub node.