Quality-driven deep feature representation learning and its industrial application to soft sensors

Author:

Song Xiao-Lu,Zhang Ning,Shi Yilin,He Yan-Lin,Xu Yuan,Zhu Qun-XiongORCID

Funder

China Scholarship Council

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference31 articles.

1. Attention-based interval aided networks for data modeling of heterogeneous sampling sequences with missing values in process industry;Yuan;IEEE Trans. Ind. Inform.,2023

2. Novel virtual sample generation method based on data augmentation and weighted interpolation for soft sensing with small data;Song;Expert Syst. Appl.,2023

3. A two-phase soft sensor modeling framework for quality prediction in industrial processes with missing data;Ma;J. Process Control,2023

4. Flexible clockwork recurrent neural network for multirate industrial soft sensor;Chang;J. Process Control,2022

5. A data-driven self-supervised LSTM-DeepFM model for industrial soft sensor;Ren;IEEE Trans. Ind. Inform.,2021

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