Tag: traffic forecasting

Researchers trained a deep learning model on raw noisy traffic windows to predict expert-filtered targets, cutting forecast errors against the ...

A condition-stratified study of westbound Interstate I-94 found that XGBoost without weather variables delivered the most accurate hour-ahead traffic forecasts.

A new dynamic graph neural framework called GAMMA-Traffic updates road-network connections in real time using cross-correlation analysis, reporting up to ...

Malaysian researchers have built a hybrid CNN-LSTM traffic forecasting system that pairs deep learning accuracy with Formal Concept Analysis to ...

Researchers in Cairo have developed a hybrid CNN–BiLSTM deep learning model fed by IoT sensor data that forecasts urban traffic ...

Researchers in Hangzhou have developed MGCRN, a graph-based recurrent neural network that maintains high forecasting accuracy on spatio-temporal data even ...

NYU Tandon researchers have built a locally hosted GeoAI framework that combines LSTM traffic forecasting, hexagonal spatial mapping and a ...

Researchers have developed a graph neural network model that learns dynamic time delays between variables in multivariate time series, improving ...