A recent 2025 study by Chen Ying-Ting presents a model that fuses spatial and temporal data using graph convolution techniques. It compares past traffic trends, weather, and dynamic network data to improve predictions. This method can be applied in scenarios like urban congestion management to boost efficiency.
Q&A
- What is STFGCN?
- How does multi factor fusion enhance prediction?
- What are the key components of this model?