Development of a novel parallel framework upon deep dual‐enhanced autoencoder and its applications for industrial soft sensing
In recent years, data‐driven soft sensing technology has provided a cost‐effective support for industrial process monitoring, in which autoencoder plays an important role in extracting features for soft sensing technology. However, existing autoencoder models take a long time for modelling, and the...
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| Vydané v: | Canadian journal of chemical engineering |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
22.07.2025
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| ISSN: | 0008-4034, 1939-019X |
| On-line prístup: | Získať plný text |
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