Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE

In modern industrial processes, soft sensors have played an important role for effective process control, optimization, and monitoring. Feature representation is one of the core factors to construct accurate soft sensors. Recently, deep learning techniques have been developed for high-level abstract...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on industrial informatics Jg. 14; H. 7; S. 3235 - 3243
Hauptverfasser:	Yuan, Xiaofeng, Huang, Biao, Wang, Yalin, Yang, Chunhua, Gui, Weihua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.07.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Correlation analysis Data mining Deep learning Feature extraction Feature recognition Industrial applications Informatics Machine learning Monitoring Multilayers Neural networks output prediction Pattern recognition Process control Representations Sensors soft sensor stacked autoencoder (SAE) Training variable-wise weighted SAE (VW-SAE)
ISSN:	1551-3203, 1941-0050
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!