Uncovering Spatio-temporal Travel Patterns Using a Tensor-based Model from Metro Smart Card Data in Shenzhen, China
Abstract
Individual mobility patterns are an important factor in urban traffic planning and traffic flow forecasting. How to understand the spatio-temporal distribution of passengers deeply and accurately, so as to provide theoretical support for the planning and operation of the metro network, is an urgent issue of wide concern. In this paper, we applied NCP decomposition to uncover the characteristics of travel patterns from temporal and spatial...
Paper Details
Title
Uncovering Spatio-temporal Travel Patterns Using a Tensor-based Model from Metro Smart Card Data in Shenzhen, China
Published Date
Feb 17, 2020
Journal
Volume
12
Issue
4
Pages
1475 - 1475
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