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Estimating wildlife strike costs at US airports: A machine learning approach
Machine learning approach to ship fuel consumption: A case of container vessel
Exploring nonlinear effects of the built environment on ridesplitting: Evidence from Chengdu
Using ultrasound images of the forearm to predict finger positions
Learning efficient haptic shape exploration with a rigid tactile sensor array
Gaussian process regression for forecasting battery state of health
Examining threshold effects of built environment elements on travel-related carbon-dioxide emissions
Non-linear associations between the built environment and the physical activity of children
Examining nonlinear and interaction effects of multiple determinants on airline travel satisfaction
Nonlinear effects of the built environment on metro-integrated ridesourcing usage
Machine learning estimates of plug-in hybrid electric vehicle utility factors
Modeling time-of-day car use behavior: A Bayesian network approach
Using explainable machine learning to understand how urban form shapes sustainable mobility
A Multiagency Long Short-Term Model Beamforming Prediction Model for Cellular Vehicle to Everything
Spatial disparity of individual and collective walking behaviors: A new theoretical framework
Sharing behavior in ride-hailing trips: A machine learning inference approach
GraphCast for solving the air transportation nexus among safety, efficiency, and resilience
Illustrating nonlinear effects of built environment attributes on housing renters’ transit commuting
Radar Waveforms and Their Mathematical Models
Gender differences in active travel among older adults: Non-linear built environment insights
Joint associations of environmental and sociodemographic attributes with active and sedentary travel
Exploring user satisfaction and improvement priorities in electric vehicle segments
Exploring the nonlinear effects of built environment characteristics on customized bus service
Vehicular Networks and Autonomous Driving Cars
Detection & Tracking of Multi-Scenic Lane Based on Segnet-LSTM Semantic Split Network
Studying the capabilities of the analytical system based on the machine learning method
A Real-World Data-Driven approach for estimating environmental impacts of traffic accidents
Revisiting residential self-selection and travel behavior connection using a double machine learning
Analysis and estimation of energy consumption of electric buses using real-world data
Exploring nonlinear built environment effects on driving with a mixed-methods approach
Fake it till you make it: Synthetic data for emerging carsharing programs
A time series clustering based approach for construction of real-world drive cycles
Target Recognition and Classification Techniques
Driving the environmental extra mile – Car sharing and voluntary carbon dioxide offsetting
Optimization of Antenna Coupling through Machine Learning for “Smart” TPMS Readers
An Electric Vehicle Transitioning Framework for Public Fleet Planning