Unsupervised Pattern Discovery in Automotive Time Series is popular PDF and ePub book, written by Fabian Kai Dietrich Noering in 2022-03-23, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Unsupervised Pattern Discovery in Automotive Time Series can be Read Online from any device for your convenience.
Unsupervised Pattern Discovery in Automotive Time Series Book PDF 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.
Detail Book of Unsupervised Pattern Discovery in Automotive Time Series PDF
- Author : Fabian Kai Dietrich Noering
- Release : 23 March 2022
- Publisher : Springer Nature
- ISBN : 9783658363369
- Genre : Technology & Engineering
- Total Page : 165 pages
- Language : English
- PDF File Size : 19,9 Mb
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