| ISBN13: | 9789819989164 |
| ISBN10: | 9819989167 |
| Kötéstípus: | Keménykötés |
| Terjedelem: | 554 oldal |
| Méret: | 235x155 mm |
| Nyelv: | angol |
| Illusztrációk: | 76 Illustrations, black & white; 281 Illustrations, color |
| 700 |
A mérnöki tudományok általános kérdései
Rendszeranalízis, rendszertervezés
Operációs rendszerek és grafikus felhasználói felületek
Mesterséges intelligencia
A mérnöki tudományok általános kérdései (karitatív célú kampány)
Rendszeranalízis, rendszertervezés (karitatív célú kampány)
Operációs rendszerek és grafikus felhasználói felületek (karitatív célú kampány)
Mesterséges intelligencia (karitatív célú kampány)
Fault diagnosis and prognostics based on cognitive computing and geometric space transformation
EUR 235.39
Kattintson ide a feliratkozáshoz
This monograph introduces readers to new theories and methods applying cognitive computing and geometric space transformation to the field of fault diagnosis and prognostics. It summarizes the basic concepts and technical aspects of fault diagnosis and prognostics technology. Existing bottleneck problems are examined, and the advantages of applying cognitive computing and geometric space transformation are explained. In turn, the book highlights fault diagnosis, prognostic, and health assessment technologies based on cognitive computing methods, including deep learning, transfer learning, visual cognition, and compressed sensing. Lastly, it covers technologies based on differential geometry, space transformation, and pattern recognition.
This monograph introduces readers to new theories and methods applying cognitive computing and geometric space transformation to the field of fault diagnosis and prognostics. It summarizes the basic concepts and technical aspects of fault diagnosis and prognostics technology. Existing bottleneck problems are examined, and the advantages of applying cognitive computing and geometric space transformation are explained. In turn, the book highlights fault diagnosis, prognostic, and health assessment technologies based on cognitive computing methods, including deep learning, transfer learning, visual cognition, and compressed sensing. Lastly, it covers technologies based on differential geometry, space transformation, and pattern recognition.
Chapter 1 Introduction.- Chapter 2 Fault Diagnosis and Prognosis based on Deep Learning and Transfer Learning.- Chapter 3 Fault Diagnosis and Evaluation Based on Visual Cognitive Computing.- Chapter 4 Fault Diagnosis Based on Compressed Sensing.- Chapter 5 Fault Diagnosis and Evaluation Based on Differential Geometry.- Chapter 6 Performance Degradation Prediction and Assessment based on Geometric Space Transformation and Morphology Recognition.
