IEEE

Dynamic Spatial-Temporal Graph Convolutional Neural Networks Approach for Active Mode Traffic Prediction

Abstract: Accurate short-term predictions of active mode traffic are crucial for effective urban traffic control and management, helping to reduce delays, stops, and improve travel time reliability, ...
IEEE

Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks

Abstract: Wind speed forecasting is significant in practical applications such as energy dispatch and meteorological early warning systems. However, spatiotemporal correlations of wind speed are ...
GitHub

better-auth-microsoft-graph

Seamlessly integrate Better Auth with Microsoft Graph API to access user profile, calendar, contacts, mail, and OneDrive data. GET /api/auth/microsoft/me/calendar ...
Frontiers

Enhancing underwater acoustic orthogonal frequency division multiplexing based channel estimation: a robust convolution-recurrent neural network framework with dynamic signal ...

Introduction: Underwater acoustic (UWA) communication systems confront significant challenges due to the unique, dynamic, and unpredictable nature of acoustic channels, which are impacted by low ...