Graph Neural Network Model Predicts City Traffic Flow and Congestion With High Accuracy
A new open access study reports a spatio-temporal graph convolutional network that predicted traffic flow with 97.99% precision and congestion ...
A new open access study reports a spatio-temporal graph convolutional network that predicted traffic flow with 97.99% precision and congestion ...
Researchers at Dalian Maritime University have developed ESTGCN, a graph neural network that dynamically rewires regional traffic relationships to deliver ...
Researchers at Linyi University have combined wavelet decomposition with denoising diffusion models to forecast urban traffic flow more accurately across ...
Researchers in Italy have built a Granger causality-guided multi-graph transformer that sharply improves traffic flow forecasting while learning interpretable directional ...
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© 2025 Scienmag - Science Magazine