United States
Massachusetts Institute of Technology (MIT) - Center for Transportation & Logistics
Port Efficiency, Container dwell time, Short-haul rail, Intermodal transportation, Discrete event simulation (DES), Port congestion, Commodity analysis, Modal shift
Demand aggregation, Capacitated Facility Location Problem, CFLP
Highway Traffic, Metropolitan Regional Congestion, Seasonal Naive
ETSX, interpretable time series models, LSTM, machine learning
artificial neural nets, machine learning
Discrete choice, Network effects, Social interactions, Social networks
Bicycle route choice, GPS trajectory, Inverse reinforcement learning
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Clustering, GPS traces, Modularity optimization, OD-matrices
Discrete choice, Multi-agent based social simulation, Social networks
bicycle route choice, environmental variables
Choice sets, Route choice generation, Route complexity
bicycle route behavior, dynamic discrete choice, dynamic programming
Bicycle, Choice set, GPS traces, Route
Effect analysis, Logistic regression model, Logit model, Parking behavior
accessibility, activity based travel demand model, pareto optimal transit
bicycling, multi-modal networks, origin-destination matrix, pedestrians
Neural nets, Public transportation network change, Transfer learning
CNN, LSTM, Machine learning, Neural nets
Artificial neural nets, Machine learning
etsx, external variables, prediction models, quantile regression
Automatic Information System (AIS), Boosted Hybrid
Demand Forecasting, Drop Trailer Management, Gradient Boosted Trees
automated warehouse, material placement, mobile robot, optimization
I-Splines, park, ride, scenario analysis
"Harmonic regression", "Highway traffic forecasting", "Prophet", "Road maintenance", "SAR", "SARIMA", "Vehicle category"
