Dynamic dispatching system using a deep denoising autoencoder for semiconductor manufacturing

Deep denoising autoencoders (DDAE), which are variants of the autoencoder, have shown outstanding performance in various machine learning tasks. In this study, we propose using a DDAE to address a dispatching rule selection problem that represents a major problem in semiconductor manufacturing. Rece...

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Veröffentlicht in:	Applied soft computing Jg. 86; S. 105904
Hauptverfasser:	Lee, Sangmin, Kim, Hae Joong, Kim, Seoung Bum
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.01.2020
Schlagworte:	Class imbalance problem Deep denoising autoencoder Dispatching rule selection Novelty detection Storage allocation Dispatching rule selection Storage allocation Deep denoising autoencoder Novelty detection Class imbalance problem
ISSN:	1568-4946, 1872-9681
Online-Zugang:	Volltext
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