Dual Attention-Based Encoder-Decoder: A Customized Sequence-to-Sequence Learning for Soft Sensor Development

Soft sensor techniques have been applied to predict the hard-to-measure quality variables based on the easy-to-measure process variables in industry scenarios. Since the products are usually produced with prearranged processing orders, the sequential dependence among different variables can be impor...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 32; H. 8; S. 3306 - 3317
Hauptverfasser:	Feng, Liangjun, Zhao, Chunhui, Sun, Youxian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.08.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Attention mechanism Coders Customization Decoding encoder–decoder Feature extraction Humidity Industries Learning Long short-term memory long short-term memory (LSTM) network Multiphase flow Prediction algorithms Predictive models process industry Process variables Sensors sequence to sequence learning soft sensor modeling Task analysis
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!