Soft Sensor Method based on Quality-related Virtual Sample Generation and Sample-weighted Learning

In process industry, data-driven soft sensor often faces the problem of data shortage in modeling due to factors such as high cost of label samples acquisition and high data repetition rate. The virtual sample generation (VSG) method has been proposed for data augmentation to solve the above problem...

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Vydáno v:	Data Driven Control and Learning Systems Conference (Online) s. 1318 - 1324
Hlavní autoři:	Dong, Shuang, Jin, Huaiping, Wang, Bin, Yang, Biao, Liu, Haipeng
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 17.05.2024
Témata:	Accuracy Data augmentation Generative adversarial networks Industries Learning systems Linear programming Predictive models Sample-weighted learning Soft sensor Soft sensors Supervised variational autoencoder Virtual sample generation
ISSN:	2767-9861
On-line přístup:	Získat plný text
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