| 000 | 02604nam a22003255i 4500 | ||
|---|---|---|---|
| 001 | 102943 | ||
| 003 | DE-He213 | ||
| 005 | 20230102113107.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 171201s2018 gw | s |||| 0|eng d | ||
| 020 | _a9783658203672 | ||
| 024 | 7 |
_a10.1007/978-3-658-20367-2 _2doi |
|
| 040 |
_aES-MaUEC _bspa |
||
| 050 | 4 |
_aQ325.5 _bB474 2018 EB |
|
| 100 | 1 |
_aBergmeir, Philipp _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _0http://id.loc.gov/authorities/names/no2018142016 _1http://viaf.org/viaf/39151836459620401679/ |
|
| 245 | 1 | 0 |
_aEnhanced Machine Learning and Data Mining Methods for Analysing Large Hybrid Electric Vehicle Fleets based on Load Spectrum Data _cby Philipp Bergmeir. |
| 264 | 1 |
_aWiesbaden _bSpringer International Publishing _c2018 |
|
| 300 | _a1 recurso en línea (XXXII, 166 páginas 34 ilustraciones) | ||
| 347 |
_atext file _bPDF |
||
| 490 | 0 |
_aWissenschaftliche Reihe Fahrzeugtechnik Universität Stuttgart _x2567-0042 |
|
| 520 | 3 | _aPhilipp Bergmeir works on the development and enhancement of data mining and machine learning methods with the aim of analysing automatically huge amounts of load spectrum data that are recorded for large hybrid electric vehicle fleets. In particular, he presents new approaches for uncovering and describing stress and usage patterns that are related to failures of selected components of the hybrid power-train. Contents Classifying Component Failures of a Vehicle Fleet Visualising Different Kinds of Vehicle Stress and Usage Identifying Usage and Stress Patterns in a Vehicle Fleet Target Groups Students and scientists in the field of automotive engineering and data science Engineers in the automotive industry About the Author Philipp Bergmeir did a PhD in the doctoral program "Promotionskolleg HYBRID" at the Institute for Internal Combustion Engines and Automotive Engineering, University of Stuttgart, in cooperation with the Esslingen University of Applied Sciences and a well-known vehicle manufacturer. Currently, he is working as a data scientist in the automotive industry. | |
| 650 | 7 |
_aAprendizaje automático _2embne _9166090 |
|
| 650 | 7 |
_aData mining _2embne _9162648 |
|
| 776 | 0 | 8 |
_iEdición impresa: _z9783658203665 |
| 776 | 0 | 8 |
_iEdición impresa: _z9783658203689 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-658-20367-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 490 | 0 | _aEngineering (Springer-11647) | |
| 988 | _aEBSPRINGER_2018 | ||
| 998 |
_b02/2019 _dz _ek _feng _ggw _h0 |
||
| 999 |
_c102943 _d102943 _x1 |
||