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Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network
Big sensor data provide significant potential for chemical fault diagnosis, which involves the baseline values of security, stability and reliability in chemical processes. A deep neural network (DNN) with novel active learning for inducing chemical fault diagnosis is presented in this study. It is...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087483/ https://www.ncbi.nlm.nih.gov/pubmed/27754386 http://dx.doi.org/10.3390/s16101695 |