| Autor: |
Lickert, Hannah, Wewer, Aleksandra, Dittmann, Sören, Bilge, Pinar, Dietrich, Franz |
| Zdroj: |
Procedia CIRP; 2020, Vol. 96, p272-277, 6p |
| Abstrakt: |
The use of machine learning (ML) for data analysis is constantly increasing in industry. Reverse logistics, which struggles with many uncertainties related to complex processes and can benefit from implementing ML. Yet, such solutions are often not applied due to lack of common knowledge. The goal of this paper is to support a preselection of ML algorithms by developing a concept that provides a comprehensive overview of basic ML algorithms and their characteristics. Therefore, basic supervised ML algorithms and a set of criteria are selected and described, matching both in a table. The applicability of the concept is reviewed on an exemplary use case from reverse logistics. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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