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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
Real-time demand forecasting for an urban delivery platform
Generating bunkering statistics from AIS data: A machine learning approach
Data mining for quality control: Burr detection in the drilling process
Machine learning in information systems - a bibliographic review and open research issues
Hybrid Electric Vehicle Powertrain Control Based on Reinforcement Learning
Applications of machine learning methods in port operations – A systematic literature review
A novel self-organizing constructive neural network for estimating aircraft trip fuel consumption
Development of a two-stage ship fuel consumption prediction and reduction model for a dry bulk ship
Using a decision tree to compare rural versus highway motorcycle fatalities in Thailand
Artificial intelligence and machine learning
Machine learning and deep learning
A data-driven Bayesian model for evaluating the duration of detention of ships in PSC inspections