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Aircraft Landing Time Prediction with Deep Learning on Trajectory Images
Aircraft landing time (ALT) prediction is crucial for air traffic management, especially for arrival aircraft sequencing on the runway.
STGIN: A Spatial Temporal Graph-Informer Network for Long Sequence Traffic Speed Forecasting
Accurate long series forecasting of traffic information is critical for the development of intelligent traffic systems.
Dense-TNT: Efficient Vehicle Type Classification Neural Network Using Satellite Imagery
Accurate vehicle type classification serves a significant role in the intelligent transportation system.
A SUMO Framework for Deep Reinforcement Learning Experiments Solving Electric Vehicle Charging Dispatching Problem
To better serve further research on various related Deep Reinforcment Learning (DRL) EV dispatching algorithms, an efficient simulation environment is necessary to ensure success.
AST-GIN: Attribute-Augmented Spatial-Temporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting
Electric Vehicle (EV) charging demand and charging station availability forecasting is one of the challenges in the intelligent transportation system.
Edge-Aware Extended Star-Tetrix Transforms for CFA-Sampled Raw Camera Image Compression
Compared with XSTTs, the EXSTTs can decorrelate CFA-sampled raw images well: they reduce the difference in energy between the two green components by about $3. 38$--$30. 08$ \% for high-quality camera images and $8. 97$--$14. 47$ \% for mobile phone images.
New interaction potentials for alkaline earth silicate and borate glasses
Compared with calcium silicate, the higher elastic moduli of magnesium silicate result from a higher connectivity of the overall glass network due to the incorporation of fourfold coordinated magnesium and a more rigid connection between SiO4 tetrahedra and modifier ions.
Materials Science Disordered Systems and Neural Networks
