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Enhanced machine learning and data m...

Bergmeir, Philipp.

Enhanced machine learning and data mining methods for analysing large hybrid electric vehicle fleets based on load spectrum data

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Enhanced machine learning and data mining methods for analysing large hybrid electric vehicle fleets based on load spectrum databy Philipp Bergmeir.
作者:	Bergmeir, Philipp.
出版者:	Wiesbaden :Springer Fachmedien Wiesbaden :2018.
面頁冊數:	xxxii, 166 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Machine learning.
電子資源:	http://dx.doi.org/10.1007/978-3-658-20367-2
ISBN:	9783658203672$q(electronic bk.)

Enhanced machine learning and data mining methods for analysing large hybrid electric vehicle fleets based on load spectrum data
Bergmeir, Philipp.

Enhanced machine learning and data mining methods for analysing large hybrid electric vehicle fleets based on load spectrum data[electronic resource] /by Philipp Bergmeir. - Wiesbaden :Springer Fachmedien Wiesbaden :2018. - xxxii, 166 p. :ill., digital ;24 cm. - Wissenschaftliche reihe fahrzeugtechnik universitat stuttgart. - Wissenschaftliche reihe fahrzeugtechnik universitat stuttgart..

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. Contents Classifying Component Failures of a Vehicle Fleet Visualising Different Kinds of Vehicle Stress and Usage Identifying Usage and Stress Patterns in a Vehicle Fleet Target Groups Students and scientists in the field of automotive engineering and data science Engineers in the automotive industry About the Author Philipp Bergmeir did a PhD in the doctoral program "Promotionskolleg HYBRID" at the Institute for Internal Combustion Engines and Automotive Engineering, University of Stuttgart, in cooperation with the Esslingen University of Applied Sciences and a well-known vehicle manufacturer. Currently, he is working as a data scientist in the automotive industry.

ISBN: 9783658203672$q(electronic bk.)

Standard No.: 10.1007/978-3-658-20367-2doiSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Enhanced machine learning and data mining methods for analysing large hybrid electric vehicle fleets based on load spectrum data
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