A theory-informed multivariate causal framework for trustworthy short-term urban traffic forecasting
Abstract Traffic forecasting using Deep Learning has been a remarkably active and
innovative research field during the last decades. However, there are still several barriers to …
innovative research field during the last decades. However, there are still several barriers to …
Probabilistic spatio-temporal graph convolutional network for traffic forecasting
Forecasting traffic flow is crucial for Intelligent Traffic Systems (ITS), traffic control, and traffic
management systems. Complex spatial and temporal interactions of traffic networks make …
management systems. Complex spatial and temporal interactions of traffic networks make …
Data Mining in Transportation Networks with Graph Neural Networks: A Review and Outlook
Data mining in transportation networks (DMTNs) refers to using diverse types of spatio-
temporal data for various transportation tasks, including pattern analysis, traffic prediction …
temporal data for various transportation tasks, including pattern analysis, traffic prediction …
Enhancing Deep Learning-Based City-Wide Traffic Prediction Pipelines Through Complexity Analysis
Deep learning models can effectively capture the non-linear spatiotemporal dynamics of city-
wide traffic forecasting. Evidence of varying deep learning model performance between …
wide traffic forecasting. Evidence of varying deep learning model performance between …
[HTML][HTML] A Hybrid Improved Dual-Channel and Dual-Attention Mechanism Model for Water Quality Prediction in Nearshore Aquaculture
W Liu, J Wang, Z Li, Q Lu - Electronics, 2025 - mdpi.com
The aquatic environment in aquaculture serves as the foundation for the survival and growth
of aquatic animals, while a high-quality water environment is a necessary condition for …
of aquatic animals, while a high-quality water environment is a necessary condition for …
Interpretable Representation and Customizable Retrieval of Traffic Congestion Patterns Using Causal Graph-Based Feature Associations
The substantial increase in traffic data offers new opportunities to inspect traffic congestion
dynamics from different perspectives. This paper presents a novel framework for the …
dynamics from different perspectives. This paper presents a novel framework for the …
A VANET, Multi-Hop-Enabled, Dynamic Traffic Assignment for Road Networks
W Arellano, I Mahgoub - Electronics, 2025 - mdpi.com
Traffic congestion imposes burdens on society and individuals. In 2022, the average
congestion cost per auto commuter in the USA was USD1259. New possibilities to increase …
congestion cost per auto commuter in the USA was USD1259. New possibilities to increase …
Robust Traffic Prediction Using Probabilistic Spatio-Temporal Graph Convolutional Network
Accurate traffic forecasting is crucial for the effective functioning of intelligent transportation
systems (ITS). It helps in urban traffic planning, traffic management, and traffic control …
systems (ITS). It helps in urban traffic planning, traffic management, and traffic control …