The Subdivision of Railway Passenger Transport Market Based on Rough Clustering Algorithm

被引：0
|
作者：
Li H.-J. [1 ]
Li Y.-Z. [1 ]
Zhou P. [1 ]
Zhu C.-F. [1 ]
Ma C.-X. [1 ]
机构：
[1] School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou
来源：
Li, Yin-Zhen (liyz01@mail.lzjtu.cn) | 2018年 / Science Press卷 / 18期
关键词：
Cluster analysis; Market segmentation; Passenger transport market; Railway transportation; Rough set;
D O I：
10.16097/j.cnki.1009-6744.2018.03.002
中图分类号：
学科分类号：
摘要：
The subdivision of railway passenger transport market is the basis for the study of passenger flow share rate in the railway corridor and the design of railway passenger transport products. According to the survey data on passengers travel mode choice in Baoji- Lanzhou corridor, combined with rough set theory, firstly, this paper builds the railway passenger travel mode choice decision table, makes attribute reduction on condition attributes, and calculates the weight of each attribute. Secondly, to avoid the "dimension trap" caused by the traditional clustering algorithm, it proposes the K-means clustering algorithm based on rough attribute significance, and makes simulation experiments on UCI data sets. Finally, using the clustering algorithm conducts the cluster on the sample of survey data. The results show that when the railway passenger transport market is divided into 6 classes, the clustering effect is the best, and the statistical analysis shows that the passenger travel behavior of different sub markets has obvious preference. Copyright © 2018 by Science Press.
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页码：9 / 14and21
页数：1412
相关论文
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