Unsupervised pattern discovery deals with the identification of similar recurring subsequences in time series without any knowledge regarding these patterns. The unsupervised discovery of patterns in time series has proven to be beneficial in many different research areas. This thesis investigated the application of pattern discovery in automotive use cases, which was considered as a gap in research previously. The handling of automotive data, or vehicle time series data, is especially challenging because it unites properties like high dynamism, diversity, dimensionality and large sizes.
Conclusion
AutoUni – Schriftenreihe
Unsupervised Pattern Discovery in Automotive Time Series ; Kapitel : 6 ; 135-139
AutoUni – Schriftenreihe ; 159
2022-03-24
5 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Springer Verlag | 2023
|Springer Verlag | 2022
|Springer Verlag | 2011
|Springer Verlag | 2022
|Springer Verlag | 2013
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