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Fair collaborative vehicle routing: A deep multi-agent reinforcement learning approach
Machine learning approach to ship fuel consumption: A case of container vessel
Trustworthy safety improvement for autonomous driving using reinforcement learning
Safer tomorrow: Irish dairy farmers’ self-perception of their farm safety practices
Learning and managing stochastic network traffic dynamics with an aggregate traffic representation
Imbalanced satellite telemetry data anomaly detection model based on Bayesian LSTM
Scalable reinforcement learning approaches for dynamic pricing in ride-hailing systems
Towards efficient airline disruption recovery with reinforcement learning
Exploring nonlinear effects of the built environment on ridesplitting: Evidence from Chengdu
DeepTrend 2.0: A light-weighted multi-scale traffic prediction model using detrending
A data-driven decision support system for service completion prediction in last mile logistics
University based interdisciplinary space lab: Designing for astronaut health and wellbeing
Computer-based training for safety: Comparing methods with older and younger workers
Dynamic modelling of travellers’ social interactions and social learning
Factors impacting bike crash severity in urban areas
Improving seat belt use among teen drivers: Findings from a service-learning approach
Applying deep learning models to twitter data to detect airport service quality
A random forest algorithm for nowcasting of intense precipitation events
A data-driven operational model for traffic at the Dallas Fort Worth International Airport
Semi-supervised route choice modeling with sparse Automatic vehicle identification data
An effective spatial-temporal attention based neural network for traffic flow prediction
Recurrent and convolutional neural networks for deep terrain classification by autonomous robots
A literature review of machine learning algorithms for crash injury severity prediction
Understanding ridesplitting behavior of on-demand ride services: An ensemble learning approach
Path planning for asteroid hopping rovers with pre-trained deep reinforcement learning architectures