Classification Method of Urban Rail Transit Emergencies Based on Improved K-means Algorithm

被引：0

作者：

Zheng X.-C. ^{[1
,3
]}

Wei Y. ^{[1
,3
]}

Qin Y. ^{[2
]}

Wang M.-M. ^{[2
]}

Chen M.-D. ^{[1
,3
]}

Zhao H.-W. ^{[1
]}

机构：

[1] Beijing Urban Construction Design & Development Group Co. Limited, Beijing

[2] School of Traffic and Transportation, Beijing Jiaotong University, Beijing

[3] National Engineering Laboratory for Green & Safe Construction Technology in Urban Rail Transit, Beijing

来源：

Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2019年 / 19卷 / 03期

基金：

国家重点研发计划;

关键词：

Classification; Emergency; K-means clustering; Principal component analysis; Traffic engineering;

D O I：

10.16097/j.cnki.1009-6744.2019.03.020

中图分类号：

学科分类号：

摘要：

This paper presents an improved K-means clustering method for urban rail transit emergencies. Firstly, the characteristics of various types of events are analyzed from the aspects of event type, duration and degree of influence, and 8 key features are extracted for cluster analysis. Secondly, principal component analysis is proposed to extract 4 principal component variables and the weighting coefficient of original variables is calculated. An initial clustering center determination method based on density scanning is proposed, and the improved K-means clustering algorithm is applied to the classification of subway emergency events. Case results show that compared with the original K-means clustering method, the improved method proposed in this paper has better clustering effect. The results were applied in the Beijing subway emergency command system, which verified the feasibility of the method. Copyright © 2019 by Science Press.

引用

页码：134 / 140

页数：6

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