A survey on deep learning for human mobility

M Luca, G Barlacchi, B Lepri… - ACM Computing Surveys …, 2021 - dl.acm.org
The study of human mobility is crucial due to its impact on several aspects of our society,
such as disease spreading, urban planning, well-being, pollution, and more. The …

[HTML][HTML] Utilizing machine learning on freight transportation and logistics applications: A review

K Tsolaki, T Vafeiadis, A Nizamis, D Ioannidis… - ICT Express, 2023 - Elsevier
This review article explores and locates the current state-of-the-art related to application
areas from freight transportation, supply chain and logistics that focuses on arrival time …

PMF: A privacy-preserving human mobility prediction framework via federated learning

J Feng, C Rong, F Sun, D Guo, Y Li - … of the ACM on Interactive, Mobile …, 2020 - dl.acm.org
With the popularity of mobile devices and location-based social network, understanding and
modelling the human mobility becomes an important topic in the field of ubiquitous …

TrajGAIL: Generating urban vehicle trajectories using generative adversarial imitation learning

S Choi, J Kim, H Yeo - Transportation Research Part C: Emerging …, 2021 - Elsevier
Recently, an abundant amount of urban vehicle trajectory data has been collected in road
networks. Many studies have used machine learning algorithms to analyze patterns in …

Scikit-mobility: A Python library for the analysis, generation, and risk assessment of mobility data

L Pappalardo, F Simini, G Barlacchi… - Journal of Statistical …, 2022 - jstatsoft.org
The last decade has witnessed the emergence of massive mobility datasets, such as tracks
generated by GPS devices, call detail records, and geo-tagged posts from social media …

Deep learning for trajectory data management and mining: A survey and beyond

W Chen, Y Liang, Y Zhu, Y Chang, K Luo… - arxiv preprint arxiv …, 2024 - arxiv.org
Trajectory computing is a pivotal domain encompassing trajectory data management and
mining, garnering widespread attention due to its crucial role in various practical …

Mobility prediction: A survey on state-of-the-art schemes and future applications

H Zhang, L Dai - IEEE access, 2018 - ieeexplore.ieee.org
Recently, mobility has gathered tremendous interest as the users' desire for consecutive
connections and better quality of service has increased. An accurate prediction of user …

An efficient LSTM neural network-based framework for vessel location forecasting

E Chondrodima, N Pelekis, A Pikrakis… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Forecasting vessel locations is of major importance in the maritime domain, with
applications in safety, logistics, etc. Nowadays, vessel tracking has become possible largely …

Towards urban general intelligence: A review and outlook of urban foundation models

W Zhang, J Han, Z Xu, H Ni, H Liu, H **ong - arxiv preprint arxiv …, 2024 - arxiv.org
Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …

Machine learning for service migration: a survey

N Toumi, M Bagaa, A Ksentini - IEEE Communications Surveys …, 2023 - ieeexplore.ieee.org
Future communication networks are envisioned to satisfy increasingly granular and dynamic
requirements to accommodate the application and user demands. Indeed, novel immersive …