ADCT-Net: Adaptive traffic forecasting neural network via dual-graphic cross-fused transformer

A new approach based on association rules to add explainability to time series forecasting models

(2023) A.R. Troncoso-García et al.   Information Fusion

Integrating the traffic science with representation learning for city-wide network congestion prediction

(2023) Wenqing Zheng et al.   Information Fusion

A novel distributed forecasting method based on information fusion and incremental learning for streaming time series

(2023) Laura Melgar-García et al.   Information Fusion

MST-GAT: A multimodal spatial-temporal graph attention network for time series anomaly detection

(2022) Chaoyue Ding et al.   Information Fusion

Attention based spatiotemporal graph attention networks for traffic flow forecasting

(2022) Yi Wang et al.   INFORMATION SCIENCES

Shape-Former: Bridging CNN and Transformer via ShapeConv for multimodal image matching

(2022) Jiaxuan Chen et al.   Information Fusion

Introduction of a Simple Estimation Method for Lane-Based Queue Lengths with Lane-changing Movements

(2022) Shenura Jayatilleke et al.   Journal of The Institution of Engineers (India): Series A

Hybrid deep learning models for traffic prediction in large-scale road networks

(2022) Ge Zheng et al.   Information Fusion

A graph attention fusion network for event-driven traffic speed prediction

(2022) Zekun Qiu et al.   INFORMATION SCIENCES

Meta Graph Transformer: A Novel Framework for Spatial–Temporal Traffic Prediction

(2021) Xue Ye et al.   NEUROCOMPUTING

Learning Dynamic and Hierarchical Traffic Spatiotemporal Features With Transformer

(2021) Haoyang Yan et al.   IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS