Unsupervised pattern discovery in automotive time series : pattern-based construction of representative driving cycles / Fabrian Kai Dietrich Noering.
Noering, Fabian Kai Dietrich, author.
2022
TL152.5 .N64 2022
Available Online

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Title Unsupervised pattern discovery in automotive time series : pattern-based construction of representative driving cycles / Fabrian Kai Dietrich Noering.
Author Noering, Fabian Kai Dietrich, author.
ISBN 9783658363369 (electronic bk.)
3658363363 (electronic bk.)
9783658363352
3658363355
DOI https://doi.org/10.1007/978-3-658-36336-9
Published Wiesbaden : Springer Vieweg, [2022]
Copyright ©2022
Language English
Description 1 online resource : illustrations (some color).
Item Number 10.1007/978-3-658-36336-9 doi
Call Number TL152.5 .N64 2022
Dewey Decimal Classification 629.28/3
Summary In the last decade unsupervised pattern discovery in time series, i.e. the problem of finding recurrent similar subsequences in long multivariate time series without the need of querying subsequences, has earned more and more attention in research and industry. Pattern discovery was already successfully applied to various areas like seismology, medicine, robotics or music. Until now an application to automotive time series has not been investigated. This dissertation fills this desideratum by studying the special characteristics of vehicle sensor logs and proposing an appropriate approach for pattern discovery. To prove the benefit of pattern discovery methods in automotive applications, the algorithm is applied to construct representative driving cycles. About the author Fabian Kai Dietrich Noering is currently working in the technical development of Volkswagen AG as data scientist with a special interest in the analysis of time series regarding e.g. product optimization.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed April 6, 2022).
Series AutoUni-Schriftenreihe ; Band 159. 2512-1154
Available in Other Form Print version: 9783658363352
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Introduction
RelatedWork
Development of Pattern Discovery Algorithms for Automotive Time Series
Pattern-based Representative Cycles
Evaluation
Conclusion.

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