A Short Survey of Human Mobility Prediction in Epidemic Modeling from Transformers to LLMs
This paper provides a comprehensive survey of recent advancements in leveraging
machine learning techniques, particularly Transformer models, for predicting human mobility …
machine learning techniques, particularly Transformer models, for predicting human mobility …
Instruction-Tuning Llama-3-8B Excels in City-Scale Mobility Prediction
Human mobility prediction plays a critical role in applications such as disaster response,
urban planning, and epidemic forecasting. Traditional methods often rely on designing …
urban planning, and epidemic forecasting. Traditional methods often rely on designing …
The Story of Mobility: Combining State Space Models and Transformers for Multi-Step Trajectory Prediction
Machine learning models for predicting human mobility often require large datasets for
training, which are not always available. As a result, methods capable of learning from …
training, which are not always available. As a result, methods capable of learning from …
CrossBag: A Bag of Tricks for Cross-City Mobility Prediction
Access to large-scale human trajectory data has significantly advanced the understanding of
human mobility (HuMob) behavior for urban planning. However, these data are often …
human mobility (HuMob) behavior for urban planning. However, these data are often …
Human Mobility Challenge: Are Transformers Effective for Human Mobility Prediction?
Transformer-based models are popular for time series forecasting and spatiotemporal
prediction due to their ability to infer semantic correlations in long sequences. However, for …
prediction due to their ability to infer semantic correlations in long sequences. However, for …
Time-series Stay Frequency for Multi-City Next Location Prediction using Multiple BERTs
Human Mobility Prediction Challenge 2024 was organized to compare human future
movement prediction methods using a unified dataset. The challenge focuses on human …
movement prediction methods using a unified dataset. The challenge focuses on human …
Urban Human Mobility Prediction Using Support Vector Regression: A Classical Data-Driven Approach
Y Imai, T Tokumoto, K Koyama, T Ochi, S Imai… - Proceedings of the 2nd …, 2024 - dl.acm.org
This paper presents an efficient method for predicting human mobility trajectories in urban
areas of Japan, developed for the Hu-MobChallenge2024. Utilizing large-scale human …
areas of Japan, developed for the Hu-MobChallenge2024. Utilizing large-scale human …
Cross-city-aware Spatiotemporal BERT
M Suzuki, Y Fukushima, R Koyama… - Proceedings of the 2nd …, 2024 - dl.acm.org
Predicting human mobility has been actively studied for the past decade because of its
various possible applications, such as traffic optimization and urban planning. Despite the …
various possible applications, such as traffic optimization and urban planning. Despite the …
Human Mobility Prediction using Personalized Spatiotemporal Models
M Suzuki - Proceedings of the 2nd ACM SIGSPATIAL International …, 2024 - dl.acm.org
In this paper, I propose personalized spatiotemporal models based human mobility
prediction method. The proposed method consists of three steps. Step1: we sin-cos …
prediction method. The proposed method consists of three steps. Step1: we sin-cos …
Multiple Systems Combination to Improve Human Mobility Prediction
K Yasuda, S Nukaya, N Horie, D Kamisaka - Proceedings of the 2nd …, 2024 - dl.acm.org
This paper describes a human mobility prediction system which build by KDDI Research,
Inc. to submit for Human Mobility Prediction Challenge (HuMob Challenge) 2024. The …
Inc. to submit for Human Mobility Prediction Challenge (HuMob Challenge) 2024. The …