Missing-Data Imputation With Position-Encoding Denoising Autoencoders for Industrial Processes
Author:
Affiliation:
1. School of Automation, Central South University, Changsha, China
2. Department of Automation Engineering, Technical University of Ilmenau, Ilmenau, Germany
3. School of Engineering, Huzhou University, Huzhou, China
Funder
Program of National Natural Science Foundation of China
Program of Foundation of Hunan, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/19/10367905/10637251.pdf?arnumber=10637251
Reference43 articles.
1. A Layer-Wise Data Augmentation Strategy for Deep Learning Networks and Its Soft Sensor Application in an Industrial Hydrocracking Process
2. Modelling the strip thickness in hot steel rolling mills using least-squares support vector machines
3. Quality Prediction Modeling for Industrial Processes Using Multiscale Attention-Based Convolutional Neural Network
4. Distributed Robust Process Monitoring Based on Optimized Denoising Autoencoder With Reinforcement Learning
5. A Novel Echo State Network and Its Application in Temperature Prediction of Exhaust Gas From Hot Blast Stove
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