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Lithological mapping of Nidar ophiolite complex, Ladakh using high-resolution data
Modeling and predicting vehicle accident occurrence in Chattanooga, Tennessee
Estimating wildlife strike costs at US airports: A machine learning approach
Prediction of aircraft performances based on data collected by air traffic control centers
An explainable machine learning approach to improve take-off time predictions
GIS-based ensemble soft computing models for landslide susceptibility mapping
Traffic campaigns and overconfidence: An experimental approach
Keep it simple stupid! A non-parametric kernel regression approach to forecast travel speeds
Machine learning approach to ship fuel consumption: A case of container vessel
Sunspot cycle prediction using Warped Gaussian process regression
Bridges across borders: A clustering approach to support EU regional policy
A data-driven decision support system for service completion prediction in last mile logistics
Exploring nonlinear effects of the built environment on ridesplitting: Evidence from Chengdu
A data-driven operational model for traffic at the Dallas Fort Worth International Airport
Using machine learning for direct demand modeling of ridesourcing services in Chicago
A random forest algorithm for nowcasting of intense precipitation events
A literature review of machine learning algorithms for crash injury severity prediction
Neural network based feedback optimal control for pinpoint landers under disturbances
Real-time demand forecasting for an urban delivery platform
A gravity assist mapping for the circular restricted three-body problem using Gaussian processes
Generating bunkering statistics from AIS data: A machine learning approach
Using satellite images of nighttime lights to predict the economic impact of COVID-19 in India
The use of machine learning improves the assessment of drug-induced driving behaviour
Driving analytics using smartphones: Algorithms, comparisons and challenges
Real-time traffic accidents post-impact prediction: Based on crowdsourcing data
Predicting passenger satisfaction in public transportation using machine learning models