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Eco-driving at signalized intersections: a parameterized reinforcement learning approach
Real-time traffic incident detection based on a hybrid deep learning model
An automatic methodology to measure drivers’ behavior in public transport
Efficient Exploitation of Existing Corporate Knowledge in Conceptual Ship Design
Forecasting road traffic conditions using a context-based random forest algorithm
Reinforcement learning-enabled genetic algorithm for school bus scheduling
A unified framework of proactive self-learning dynamic pricing for high-occupancy/toll lanes
STD-Yolov5: a ship-type detection model based on improved Yolov5
Using kinematic driving data to detect sleep apnea treatment adherence
Traffic volume prediction on low-volume roadways: a Cubist approach
Integration of machine learning and statistical models for crash frequency modeling
Asynchronous n-step Q-learning adaptive traffic signal control
Incorporating congestion patterns into spatio-temporal deep learning algorithms
Investigating an SVM-driven, one-class approach to estimating ship systems condition
Consumer learning behavior in choosing electric motorcycles
Framework for development of the Scheduler for Activities, Locations, and Travel (SALT) model