| 书目名称 | Unsupervised Pattern Discovery in Automotive Time Series |
| 副标题 | Pattern-based Constr |
| 编辑 | Fabian Kai Dietrich Noering |
| 视频video | |
| 丛书名称 | AutoUni – Schriftenreihe |
| 图书封面 |  |
| 描述 | .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... . |
| 出版日期 | Book 2022 |
| 关键词 | pattern discovery; motif discovery; unsupervised; time series; representative cycles; automotive |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-658-36336-9 |
| isbn_softcover | 978-3-658-36335-2 |
| isbn_ebook | 978-3-658-36336-9Series ISSN 1867-3635 Series E-ISSN 2512-1154 |
| issn_series | 1867-3635 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wies |
发表于 2025-3-21 18:48:02
