Unsupervised Pattern Discovery in Automotive Time Series : Pattern-based Construction of Representative Driving Cycles

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Titel
Unsupervised Pattern Discovery in Automotive Time Series Pattern-based Construction of Representative Driving Cycles
verantwortlich
Noering, Fabian Kai Dietrich (VerfasserIn)
Schriftenreihe
AutoUni – Schriftenreihe ; 159
Ausgabe
1st ed. 2022.
veröffentlicht
Wiesbaden: Springer Fachmedien Wiesbaden, 2022.
Wiesbaden: Imprint: Springer Vieweg, 2022.
Erscheinungsjahr
2022
Teil von
AutoUni – Schriftenreihe ; 159
Teil von
Springer eBook Collection
Erscheint auch als
Noering, Fabian Kai Dietrich, 1991 - , Unsupervised pattern discovery in automotive time series, Wiesbaden : Springer Vieweg, 2022, xxi, 148 Seiten
Andere Ausgaben
Unsupervised pattern discovery in automotive time series: pattern-based construction of representative driving cycles
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Zusammenfassung
Introduction -- RelatedWork -- Development of Pattern Discovery Algorithms for Automotive Time Series -- Pattern-based Representative Cycles -- Evaluation -- Conclusion.
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.
Umfang
1 Online-Ressource(XXI, 148 p. 56 illus., 19 illus. in color.)
Sprache
Englisch
Schlagworte
BK-Notation
55.20 Straßenfahrzeugtechnik
54.74 Maschinelles Sehen
ISBN
9783658363369
DOI
10.1007/978-3-658-36336-9