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Maschinelles Lernen
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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
Machine Learning im Cost Engineering des Supply Managements
Machine Learning im Cost Engineering des Supply Managements
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
Data mining for quality control: Burr detection in the drilling process
Learning efficient haptic shape exploration with a rigid tactile sensor array
Real-time demand forecasting for an urban delivery platform
Generating bunkering statistics from AIS data: A machine learning approach
Examining nonlinear and interaction effects of multiple determinants on airline travel satisfaction
Nonlinear effects of the built environment on metro-integrated ridesourcing usage
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
Machine learning in information systems - a bibliographic review and open research issues
Modeling time-of-day car use behavior: A Bayesian network approach
Machine learning estimates of plug-in hybrid electric vehicle utility factors
Using explainable machine learning to understand how urban form shapes sustainable mobility
Hybrid Electric Vehicle Powertrain Control Based on Reinforcement Learning
Illustrating nonlinear effects of built environment attributes on housing renters’ transit commuting
Applications of machine learning methods in port operations – A systematic literature review
Gender differences in active travel among older adults: Non-linear built environment insights
Spatial disparity of individual and collective walking behaviors: A new theoretical framework
Sharing behavior in ride-hailing trips: A machine learning inference approach
A novel self-organizing constructive neural network for estimating aircraft trip fuel consumption
Joint associations of environmental and sociodemographic attributes with active and sedentary travel
Using a decision tree to compare rural versus highway motorcycle fatalities in Thailand
Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship
Exploring user satisfaction and improvement priorities in electric vehicle segments
Artificial intelligence and machine learning
A data-driven Bayesian model for evaluating the duration of detention of ships in PSC inspections
Revisiting residential self-selection and travel behavior connection using a double machine learning
Exploring the nonlinear effects of built environment characteristics on customized bus service
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
A Real-World Data-Driven approach for estimating environmental impacts of traffic accidents
Feature subset selection for predicting the success of crowdfunding project campaigns
A time series clustering based approach for construction of real-world drive cycles
Hierarchical fault diagnosis and health monitoring in multi-platform space systems