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Sintering Quality Prediction Model Based on Semi-Supervised Dynamic Time Feature Extraction Framework
In the sintering process, it is difficult to obtain the key quality variables in real time, so there is lack of real-time information to guide the production process. Furthermore, these labeled data are too few, resulting in poor performance of conventional soft sensor models. Therefore, a novel sem...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371414/ https://www.ncbi.nlm.nih.gov/pubmed/35957415 http://dx.doi.org/10.3390/s22155861 |