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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
Gain Customer Insights Using NLP Techniques
Exploring nonlinear effects of the built environment on ridesplitting: Evidence from Chengdu
Learning efficient haptic shape exploration with a rigid tactile sensor array
Machine Learning Models for Predicting Grinding Wheel Conditions Using Acoustic Emission Features
Real-time demand forecasting for an urban delivery platform
Generating bunkering statistics from AIS data: A machine learning approach
Predictive Modeling of Aircraft Dynamics Using Neural Networks
Nonlinear effects of the built environment on metro-integrated ridesourcing usage
Examining threshold effects of built environment elements on travel-related carbon-dioxide emissions
Data mining for quality control: Burr detection in the drilling process
Multi-part Analysis and Techniques for Air Traffic Speech Recognition
Preliminary evidence of dynamic muscular synergies in human grasping
Examining nonlinear and interaction effects of multiple determinants on airline travel satisfaction