Extracting Commuting Patterns in Railway Networks through Matrix Decompositions

被引：0

作者：

Jere, Shashank ^{[1
]}

Dauwels, Justin ^{[1
]}

Asif, Muhammad Tayyab ^{[1
]}

Mitrovic, Nikola ^{[1
]}

Cichocki, Andrzej ^{[2
]}

Jaillet, Patrick ^{[3
,4
]}

机构：

[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, Singapore

[2] RIKEN, Lab Adv Brain Signal Proc, Wako, Saitama, Japan

[3] MIT, Lab Informat & Decis Syst, Cambridge, MA 02139 USA

[4] Singapore MIT Alliance Res & Technol, Ctr Future Urban Mobil, Singapore, Singapore

来源：

2014 13TH INTERNATIONAL CONFERENCE ON CONTROL AUTOMATION ROBOTICS & VISION (ICARCV) | 2014年

基金：

新加坡国家研究基金会;

关键词：

ORIGIN-DESTINATION MATRICES;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the rise in the population of the world's cities, understanding the dynamics of commuters' transportation patterns has become crucial in the planning and management of urban facilities and services. In this study, we analyze how commuter patterns change during different time instances such as between weekdays and weekends. To this end, we propose two data mining techniques, namely Common Orthogonal Basis Extraction (COBE), and Joint and Individual Variation Explained (JIVE) for Integrated Analysis of Multiple Data Types and apply them to smart card data available for passengers in Singapore. We also discuss the issues of model selection and interpretability of these methods. The joint and individual patterns can help transportation companies optimize their resources in light of changes in commuter mobility behavior.

引用

页码：541 / 546

页数：6

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