Profiling Public Transit Passenger Mobility Using Adversarial Learning

Profiling Public Transit Passenger Mobility Using Adversarial Learning

It is important to capture passengers’ public transit behavior and their mobility to create profiles, which are critical for analyzing human activities, understanding the social and economic structure of cities, improving public transportation, assisting urban planning, and promoting smart cities. I...

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Bibliographic Details
Main Authors: Yicong Li, Tong Zhang, Xiaofei Lv, Yingxi Lu, Wangshu Wang
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:ISPRS International Journal of Geo-Information
Subjects:
transit mobility embedding
generative adversarial network
smart card data
public transit
Online Access:https://www.mdpi.com/2220-9964/12/8/338

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https://www.mdpi.com/2220-9964/12/8/338

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