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Framework for development of the Scheduler for Activities, Locations, and Travel (SALT) model
DLW-Net model for traffic flow prediction under adverse weather
Assessing influential factors for lane change behavior using full real-world vehicle-by-vehicle data
Estimating cycle-level real-time traffic movements at signalized intersections
Development of a novel engine power model to estimate heavy-duty truck fuel consumption
Electric vehicle charging demand forecasting using deep learning model
Extreme wave height detection based on the meteorological data, using hybrid NOF-ELM method
Bayesian and machine learning-based fault detection and diagnostics for marine applications