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Artificial intelligence tools : decision support systems in condition monitoring and diagnosis /
Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource:Addresses nearest-neighbor-based, clustering-based, statistical, and informatio...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton, FL :
CRC Press, Taylor & Francis Group,
[2015]
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Pascual, Diego Galar, |e author. | |
| 245 | 1 | 0 | |a Artificial intelligence tools : |b decision support systems in condition monitoring and diagnosis / |c Diego Galar Pascual. |
| 264 | 1 | |a Boca Raton, FL : |b CRC Press, Taylor & Francis Group, |c [2015] | |
| 300 | |a 1 online resource : |b illustrations | ||
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| 588 | 0 | |a Online resource; title from PDF title page (Ebsco, viewed April 27, 2015). | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a 1. Massive field data collection : issues and challenges -- 2. Condition monitoring : available techniques -- 3. Challenges of condition monitoring using AI techniques -- 4. Input and output data -- 5. Two-stage response surface approaches to modeling drug interaction -- 6. Nearest neighbor-based techniques -- 7. Cluster-based techniques -- 8. Statistical techniques -- 9. Information theory-based techniques -- 10. Uncertainty management. | |
| 520 | |a Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box approaches to fault diagnosis in condition monitoring (CM). This indispensable resource:Addresses nearest-neighbor-based, clustering-based, statistical, and information theory-based techniquesConsiders the merits of each technique as well as the issues associated with real-life applicationCovers classification methods, from neural networks to Bayesian and support vector machinesProposes fuzzy logic to explain the uncertainties associated with diagnostic processes. | ||
| 546 | |a English. | ||
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| 650 | 0 | |a Maintenance |x Management |x Data processing. | |
| 650 | 0 | |a Service life (Engineering) | |
| 650 | 0 | |a Industrial equipment |x Maintenance and repair |x Data processing. | |
| 650 | 0 | |a Machinery |x Monitoring. | |
| 650 | 0 | |a Artificial intelligence |x Industrial applications. | |
| 650 | 6 | |a Entretien |x Gestion |x Informatique. | |
| 650 | 6 | |a Durée de vie (Ingénierie) | |
| 650 | 6 | |a Entreprises |x Équipement |x Entretien et réparations |x Informatique. | |
| 650 | 6 | |a Machines |x Surveillance. | |
| 650 | 6 | |a Intelligence artificielle |x Applications industrielles. | |
| 650 | 7 | |a durability. |2 aat | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Facility Management. |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Management Science. |2 bisacsh | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Organizational Behavior. |2 bisacsh | |
| 650 | 7 | |a Artificial intelligence |x Industrial applications |2 fast | |
| 650 | 7 | |a Industrial equipment |x Maintenance and repair |x Data processing |2 fast | |
| 650 | 7 | |a Machinery |x Monitoring |2 fast | |
| 650 | 7 | |a Service life (Engineering) |2 fast | |
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| 776 | 0 | 8 | |i Print version: |a Pascual, Diego Galar. |t Artificial intelligence tools. |d Boca Raton, FL : CRC Press, ©2015 |z 146658405X |w (OCoLC)881440915 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=1707786 |z Texto completo |
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