Analyzing spatial heterogeneity of ridesourcing usage determinants using explainable machine learning
There is a pressing need to study spatial heterogeneity of ridesourcing usage determinants
to develop better-targeted transportation and land use policies. This study incorporates …
to develop better-targeted transportation and land use policies. This study incorporates …
[HTML][HTML] Situational-aware multi-graph convolutional recurrent network (sa-mgcrn) for travel demand forecasting during wildfires
Natural hazards, such as wildfires, pose a significant threat to communities worldwide. Real-
time forecasting of travel demand during wildfire evacuations is crucial for emergency …
time forecasting of travel demand during wildfire evacuations is crucial for emergency …
A survey on spatio-temporal series prediction with deep learning: taxonomy, applications, and future directions
F Sun, W Hao, A Zou, Q Shen - Neural Computing and Applications, 2024 - Springer
With the rapid development of data acquisition and storage technology, spatio-temporal (ST)
data in various fields are growing explosively, so many ST prediction methods have …
data in various fields are growing explosively, so many ST prediction methods have …
[HTML][HTML] Meta-analysis of shared micromobility ridership determinants
Shared micromobility (SμM)—shared e-scooters and (e-) bikes—offer moderate-speed,
space-efficient, and carbon-light mobility, promoting environmental sustainability and …
space-efficient, and carbon-light mobility, promoting environmental sustainability and …
Analyzing shared e-scooter trip frequency on urban road segments in Austin, TX
The expansion of e-scooter sharing system presents a mix of advantages and challenges to
the urban transportation system. This research delves into the frequency of shared e-scooter …
the urban transportation system. This research delves into the frequency of shared e-scooter …
Exploring spatial heterogeneity of e-scooter's relationship with ridesourcing using explainable machine learning
The expansion of e-scooter sharing system has introduced several novel interactions within
the existing transportation system. However, few studies have explored how spatial contexts …
the existing transportation system. However, few studies have explored how spatial contexts …
Spatiotemporal forecasting using multi-graph neural network assisted dual domain transformer for wind power
G Hou, Q Li, C Huang - Energy Conversion and Management, 2025 - Elsevier
Accurate prediction of wind power generation is crucial for operational and maintenance
decision in wind farms. With the increasing scale and capacity of turbines, incorporating both …
decision in wind farms. With the increasing scale and capacity of turbines, incorporating both …
Predicting freeway non-recurring congestion via a spatio-temporal deep learning approach
Freeway unexpected events, such as car crashes, result in non-recurring congestion, which
does not follow repetitive patterns in space and/or time and increases the challenge of …
does not follow repetitive patterns in space and/or time and increases the challenge of …
Forecasting Moped Scooter-Sharing Travel Demand Using a Machine Learning Approach
The increasing popularity of moped scooter-sharing as a direct and eco-friendly
transportation option highlights the need to understand travel demand for effective urban …
transportation option highlights the need to understand travel demand for effective urban …
Travel demand forecasting: A fair ai approach
Artificial Intelligence (AI) and machine learning have been increasingly adopted for travel
demand forecasting. The AI-based travel demand forecasting models, though generate …
demand forecasting. The AI-based travel demand forecasting models, though generate …