Automated feature learning for nonlinear process monitoring – An approach using stacked denoising autoencoder and k-nearest neighbor rule

•Automated feature learning based on stacked denoising autoencoder (SDAE) and k-nearest neighbor rule (kNN) for nonlinear process monitoring.•SDAE is used to automatically learn the patterns inherent in the nonlinear process and extract key features.•New monitoring statistics that are HD2 and RD2 ar...

Celý popis

Podrobná bibliografie

Vydáno v:	Journal of process control Ročník 64; s. 49 - 61
Hlavní autoři:	Zhang, Zehan, Jiang, Teng, Li, Shuanghong, Yang, Yupu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.04.2018
Témata:	Automated feature learning Deep learning k-Nearest neighbor rule Nonlinear process monitoring Stacked denoising autoencoder Deep learning Nonlinear process monitoring Stacked denoising autoencoder Automated feature learning k-Nearest neighbor rule
ISSN:	0959-1524, 1873-2771
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!