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A hybrid Markov-based model for human mobility prediction · Study

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ArticleA hybrid Markov-based model for human mobility prediction

Yuanyuan Qiao2017

Article2017

A hybrid Markov-based model for human mobility prediction

Yuanyuan Qiao · Zhongwei Si · Yanting Zhang · Fehmi Ben Abdesslem · Jie Yang

91 citations·0/0 files stored·Neurocomputing

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Human Mobility and Location-Based Analysis Data Management and Algorithms Traffic Prediction and Management Techniques

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References

2008Understanding individual human mobility patterns 2006The scaling laws of human travel 2010Modelling the scaling properties of human mobility 2003Using GPS to learn significant locations and predict movement across multiple users 2013Unravelling daily human mobility motifs 2014From mobile phone data to the spatial structure of cities 2012Predicting future locations with hidden Markov models 2014Estimating human trajectories and hotspots through mobile phone data

Cited by

2021Mobility Prediction Using a Weighted Markov Model Based on Mobile User Classification 2021Spatio-Temporal Urban Knowledge Graph Enabled Mobility Prediction 2022Beyond The Limits of Predictability in Human Mobility Prediction: Context-Transition Predictability 2021Attentional Markov Model for Human Mobility Prediction 2020Human Mobility Prediction Using Sparse Trajectory Data 2021MDLF: A Multi-View-Based Deep Learning Framework for Individual Trip Destination Prediction in Public Transportation Systems

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Details

Year2017

Typearticle

Published2017-09-05

VenueNeurocomputing

ISSN-L0925-2312

Languageen

Citations91

Files0 public / 0

ShelfHuman Mobility and Location-Based Analysis

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doi10.1016/j.neucom.2017.05.101

openalex_workW2753140366

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2025A review of human mobility: Linking data, models, and real-world applications

2021WiFiMod: Transformer-based Indoor Human Mobility Modeling using Passive Sensing