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Unsupervised process monitoring and fault diagnosis with machine learning methods
This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-...
| Autores principales: | , |
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| Lenguaje: | eng |
| Publicado: |
Springer
2013
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| Materias: | |
| Acceso en línea: | http://cds.cern.ch/record/1606351 |