A comparative study of statistical machine learning methods for condition monitoring of electric drive trains in supply chains

Fault detection and identification are critical for the accurate maintenance and management of industrial machinery. In this regard, data-driven condition monitoring models play an important role in machinery fault diagnosis and management. This study investigates the applicability of various statis...

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Veröffentlicht in:	Supply Chain Analytics Jg. 2; S. 100011
1. Verfasser:	Lahmiri, Salim
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier 01.06.2023
Schlagworte:	Discriminant analysis Fault diagnosis K-Nearest Neighbor algorithm Kernel naïve Bayes Machine learning Support vector machine
ISSN:	2949-8635, 2949-8635
Online-Zugang:	Volltext
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