Combining individual travel behaviour and collective preferences for next location prediction-Reference-Cited by-同舟云学术

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Combining individual travel behaviour and collective preferences for next location prediction

Published:2021-09-12 Issue: Volume: Page:1-23
ISSN:2324-9935
Container-title:Transportmetrica A: Transport Science
language:en
Short-container-title:Transportmetrica A: Transport Science

Author:

Li Qiuping¹²,Zou Dan¹²,Xu Yang³⁴^ORCID

Affiliation:

1. School of Geography and Planning, Sun Yat-Sen University, Guangzhou, People’s Republic of China

2. Guangdong Provincial Engineering Research Center for Public Security and Disaster, Guangzhou, People’s Republic of China

3. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong

4. The Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, People’s Republic of China

Funder

National Natural Science Foundation of China

Guangdong Basic and Applied Basic Research Foundation

Publisher

Informa UK Limited

Subject

General Engineering,Transportation

Link

https://www.tandfonline.com/doi/pdf/10.1080/23249935.2021.1968066

Reference44 articles.

1. Origin–destination trips by purpose and time of day inferred from mobile phone data

2. The influence of temporal and spatial features on the performance of next-place prediction algorithms

3. Selecting Individual and Population Models for Predicting Human Mobility

4. Human mobility prediction based on individual and collective geographical preferences

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Combining the spatiotemporal mobility patterns and MMC for next location prediction of fake base stations;Computational Urban Science;2024-08-26

2. Short-term trajectory prediction for individual metro passengers based on multi-level periodicity mining from semantic trajectory;Engineering Applications of Artificial Intelligence;2024-07

3. A Multi-Context Aware Human Mobility Prediction Model Based on Motif-Preserving Travel Preference Learning;IEEE Transactions on Intelligent Transportation Systems;2024-02

4. Vehicle Trajectory Prediction Method for Task Offloading in Vehicular Edge Computing;Sensors;2023-09-18

5. New data-driven approach to generate typologies of road segments;Transportmetrica A: Transport Science;2023-01-02

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