CITY-SCALE HUMAN MOBILITY PREDICTION MODEL BY INTEGRATING GNSS TRAJECTORIES AND SNS DATA USING LONG SHORT-TERM MEMORY

6 citations as recorded by crossref.

1. A Systematic Review of Machine Learning Techniques for GNSS Use Cases A. Siemuri et al. https://doi.org/10.1109/TAES.2022.3219366
2. Human Mobility Prediction With Region-Based Flows and Water Consumption F. Terroso-Saenz et al. https://doi.org/10.1109/ACCESS.2021.3090582
3. Nation-wide human mobility prediction based on graph neural networks F. Terroso-Sáenz & A. Muñoz https://doi.org/10.1007/s10489-021-02645-3
4. Security that Matters: General Knowledge and Correlations in the Context of Applied Satellite Navigation, Specific Interference-Events and the Use of the GNSS-Technology J. Saretzki et al. https://doi.org/10.26417/981fxj30
5. Nation-wide touristic flow prediction with Graph Neural Networks and heterogeneous open data F. Terroso Sáenz et al. https://doi.org/10.1016/j.inffus.2022.11.005
6. Individual mobility prediction by considering current traveling features and historical activity chain X. Zhang et al. https://doi.org/10.1080/10095020.2025.2455005