AMING:Adaptive-Learning Mechanism Based Missing-Value Imputation Networks Using GAN in Industrial Processes
Author:
Affiliation:
1. School of Automation, Central South University,Changsha,410083
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10606543/10606546/10606690.pdf?arnumber=10606690
Reference29 articles.
1. Missing value imputation: a review and analysis of the literature (2006–2017)
2. Blackout Missing Data Recovery in Industrial Time Series Based on Masked-Former Hierarchical Imputation Framework
3. MBGAN: An improved generative adversarial network with multi-head self-attention and bidirectional RNN for time series imputation
4. Imputation of Missing Values in Time Series Using an Adaptive-Learned Median-Filled Deep Autoencoder
5. A Layer-Wise Data Augmentation Strategy for Deep Learning Networks and Its Soft Sensor Application in an Industrial Hydrocracking Process
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