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Enhanced Machine Learning and Data Mining Methods for Analysing Large Hybrid Electric Vehicle Fleets based on Load Spectrum Data

Philipp Bergmeir

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Springer Fachmedien Wiesbaden img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Maschinenbau, Fertigungstechnik

Beschreibung

Philipp Bergmeir works on the development and enhancement of data mining and machine learning methods with the aim of analysing automatically huge amounts of load spectrum data that are recorded for large hybrid electric vehicle fleets. In particular, he presents new approaches for uncovering and describing stress and usage patterns that are related to failures of selected components of the hybrid power-train.

 

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Schlagwörter

hybrid car battery, Off-board data, vehicle usage patterns, Balanced Random Forest, Rule Learning, Classification, Logged On-board Data, stress patterns, vehicle fleet, t-Distributed Stochastic Neighbour Embedding