Modeling Large-Scale Industrial Processes by Multiple Deep Belief Networks With Lower-Pressure and Higher-Precision for Status Monitoring
Typically, fault detection using deep learning is performed based on the features extracted from only one well-trained deep model. However, our results show that large-scale data is complicated and originates from different schemas, which will cause great pressure on deep neural networks, furthermor...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8963925/ |