Heat Conduction : Basic Research / / edited by Vyacheslav S. Vikhrenko

• Record Nr.: UNINA9910138415303321
• Pubbl/distr/stampa: Rijeka, Croatia : , : InTech, , 2011
• ISBN: 953-51-6080-X
• Descrizione fisica: 1 online resource (364 pages) : illustrations
• Disciplina: 620.1
• Soggetti: Materials science
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references.

Artificial intelligence tools : decision support systems in condition monitoring and diagnosis / / Diego Galar Pascual

• Record Nr.: UNINA9910829136803321
• Autore: Pascual Diego Galar
• Pubbl/distr/stampa: Boca Raton, Florida : , : CRC Press, , [2015]; ©2015
• ISBN: 1-4987-6019-8; 0-429-10232-1; 1-4665-8406-8
• Descrizione fisica: 1 online resource (528 p.)
• Disciplina: 658.2020285
• Soggetti: Industrial equipment - Maintenance and repair - Data processing; Machinery - Monitoring; Artificial intelligence - Industrial applications
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references at the end of each chapters.
• Nota di contenuto: Front Cover; Contents; Preface; Acknowledgments; Author; Chapter 1: Massive Field Data Collection: Issues and Challenges; Chapter 2: Condition Monitoring: Available Techniques; Chapter 3: Challenges of Condition Monitoring Using AI Techniques; Chapter 4: Input and Output Data; Chapter 5: Two-Stage Response Surface Approaches to Modeling Drug Interaction; Chapter 6: Nearest Neighbor-Based Techniques; Chapter 7: Cluster-Based Techniques; Chapter 8: Statistical Techniques; Chapter 9: Information Theory-Based Techniques; Chapter 10: Uncertainty Management; Back Cover
• Sommario/riassunto: 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