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Maschinelles Lernen
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Using explainable machine learning to understand how urban form shapes sustainable mobility
Using a decision tree to compare rural versus highway motorcycle fatalities in Thailand
Uncovering the identity of Electronic Markets research through text mining techniques
Travel impedance, the built environment, and customized-bus ridership: A stop-to-stop level analysis
Transit electrification state of the art: A machine-learning based text mining approach
Time-Series fuel consumption prediction assessing delay impacts on energy using vehicular trajectory
Systematizing the lexicon of platforms in information systems: a data-driven study
Strategieplanungen für das hybride Recycling in der Automobilindustrie
Spatial disparity of individual and collective walking behaviors: A new theoretical framework
Smart Event Forecast for Seaports (SMECS) : Schlussbericht : Projektlaufzeit: 01.09.2017-29.02.2020
Smart Event Forecast for Seaports (SMECS) : Schlussbericht : Projektlaufzeit: 01.09.2017-29.02.2020
Sharing behavior in ride-hailing trips: A machine learning inference approach
Robot-human-learning for robotic picking processes
Revisiting residential self-selection and travel behavior connection using a double machine learning
Revealing influences on carsharing users’ trip distance in small urban areas
Real-time demand forecasting for an urban delivery platform
Potential of machine learning for prediction of traffic related air pollution
Nonlinear, threshold and synergistic effects of first/last-mile facilities on metro ridership
Nonlinear effects of the built environment on metro-integrated ridesourcing usage
Non-linear associations between the built environment and the physical activity of children
Modeling time-of-day car use behavior: A Bayesian network approach
Machine learning in information systems - a bibliographic review and open research issues
Machine Learning im Cost Engineering des Supply Managements
Machine Learning im Cost Engineering des Supply Managements
Machine learning estimates of plug-in hybrid electric vehicle utility factors
Machine learning approach to ship fuel consumption: A case of container vessel
Machine learning and deep learning
Learning efficient haptic shape exploration with a rigid tactile sensor array
Joint associations of environmental and sociodemographic attributes with active and sedentary travel
Individual and synergistic associations among transit allowance, land use, and transit commuting
Illustrating nonlinear effects of built environment attributes on housing renters’ transit commuting
Hybrid Electric Vehicle Powertrain Control Based on Reinforcement Learning
Hub-and-spoke network design under congestion: A learning based metaheuristic
Hierarchical fault diagnosis and health monitoring in multi-platform space systems
Greenhouse gas emission prediction on road network using deep sequence learning