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...

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Vydáno v:	IEEE transaction on neural networks and learning systems Ročník 32; číslo 8; s. 3306 - 3317
Hlavní autoři:	Feng, Liangjun, Zhao, Chunhui, Sun, Youxian
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 01.08.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	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
On-line přístup:	Získat plný text
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