Analysis of Machine Learning Approach for the modemodel in SWC Mapping in Automotive Systems
Abstract: Automotive technologies are ever-increasinglybecoming digital. Highly autonomous driving togetherwith digital E/E control mechanisms include thousandsof software applications which are called as software components. Together with the industry requirements, and rigorous software development processes, mappingof components as a software pool becomes very difficult.This article analyses and discusses the integration possiblilities of machine learning approaches to our previously introduced concept of mapping of software components through a common software pool. https://www.bibliothek.tu-chemnitz.de/ojs/index.php/cs/article/view/447
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Analysis of Machine Learning Approach for the modemodel in SWC Mapping in Automotive Systems ; volume:7 ; number:1 ; day:20 ; month:03 ; year:2021
Embedded selforganising systems ; 7, Heft 1 (20.03.2021)
- Urheber
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Khan, Owes
Shahini, Geri
Hardt, Wolfram
- DOI
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10.14464/ess.v7i1.447
- URN
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urn:nbn:de:101:1-2023032815453496064157
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 10:45 MESZ
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Beteiligte
- Khan, Owes
- Shahini, Geri
- Hardt, Wolfram
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