SVAE-WGAN-Based Soft Sensor Data Supplement Method for Process Industry

Challenges of process industry, which is characterized as hugeness of process variables in complexity of industrial environment, can be tackled effectively by the use of soft sensor technology. However, how to supplement the dataset with effective data supplement method under harsh industrial enviro...

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Vydané v:	IEEE sensors journal Ročník 22; číslo 1; s. 601 - 610
Hlavní autori:	Gao, Shiwei, Qiu, Sulong, Ma, Zhongyu, Tian, Ran, Liu, Yanxing
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.01.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Data models data supplement Datasets Decoding Feature extraction Generative adversarial networks Industries Mathematical models Model accuracy Predictive models Process variables Sensors Soft sensor SVAE-WGAN Training Wasserstein generative adversarial network
ISSN:	1530-437X, 1558-1748
On-line prístup:	Získať plný text
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