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