State-of-the-art deep learning: Evolving machine intelligence toward tomorrow's intelligent network traffic control systems

ZM Fadlullah, F Tang, B Mao, N Kato… - … Surveys & Tutorials, 2017 - ieeexplore.ieee.org
Currently, the network traffic control systems are mainly composed of the Internet core and
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …

Urban human mobility data mining: An overview

K Zhao, S Tarkoma, S Liu, H Vo - 2016 IEEE International …, 2016 - ieeexplore.ieee.org
Understanding urban human mobility is crucial for epidemic control, urban planning, traffic
forecasting systems and, more recently, various mobile and network applications …

Predicting taxi demand at high spatial resolution: Approaching the limit of predictability

K Zhao, D Khryashchev, J Freire… - … conference on Big …, 2016 - ieeexplore.ieee.org
In big cities, taxi service is imbalanced. In some areas, passengers wait too long for a taxi,
while in others, many taxis roam without passengers. Knowledge of where a taxi will …

Urban pulse: Capturing the rhythm of cities

F Miranda, H Doraiswamy, M Lage… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Cities are inherently dynamic. Interesting patterns of behavior typically manifest at several
key areas of a city over multiple temporal resolutions. Studying these patterns can greatly …

[HTML][HTML] Quantifying human mobility resilience to extreme events using geo-located social media data

KC Roy, M Cebrian, S Hasan - EPJ Data Science, 2019 - epjdatascience.springeropen.com
Mobility is one of the fundamental requirements of human life with significant societal
impacts including productivity, economy, social wellbeing, adaptation to a changing climate …

Multi-scale spatio-temporal analysis of human mobility

L Alessandretti, P Sapiezynski, S Lehmann… - PloS one, 2017 - journals.plos.org
The recent availability of digital traces generated by phone calls and online logins has
significantly increased the scientific understanding of human mobility. Until now, however …

Predicting taxi and uber demand in cities: Approaching the limit of predictability

K Zhao, D Khryashchev, H Vo - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Time series prediction has wide applications ranging from stock price prediction, product
demand estimation to economic forecasting. In this article, we treat the taxi and Uber …

Spotting trip purposes from taxi trajectories: A general probabilistic model

P Wang, G Liu, Y Fu, Y Zhou, J Li - ACM Transactions on Intelligent …, 2017 - dl.acm.org
What is the purpose of a trip? What are the unique human mobility patterns and spatial
contexts in or near the pickup points and delivery points of trajectories for a specific trip …

CellSense: Human mobility recovery via cellular network data enhancement

Z Fang, Y Yang, G Yang, Y **an, F Zhang… - Proceedings of the ACM …, 2021 - dl.acm.org
Data from the cellular network have been proved as one of the most promising way to
understand large-scale human mobility for various ubiquitous computing applications due to …

Detecting and analyzing urban centers based on the localized contour tree method using taxi trajectory data: A case study of Shanghai

M Sun, H Fan - ISPRS International Journal of Geo-Information, 2021 - mdpi.com
Urban structure is of vital importance to urban planning, transportation, economics and other
applications. Since detecting and analyzing urban centers is crucial for understanding urban …