Traffic Prediction and Management Techniques
This cluster of papers focuses on the application of deep learning, neural networks, and spatio-temporal data analysis for traffic flow prediction and forecasting in urban environments. The research covers topics such as short-term forecasting, graph convolutional networks, time series analysis, and the integration of intelligent transportation systems.
Papers listed on taxonomy pages are the top few works per node from the OpenAlex snapshot. That list is not exhaustive and is not an endorsement. The topic map and the journal registry remain separate: there is still no authoritative topic-to-venue or topic-to-organization edge. Search is a lexical lookup, not a claim that a venue publishes a topic.