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Description

The application of Bayesian Networks (BN) or Dynamic Bayesian Networks (DBN) in dependability and risk analysis is a recent development. A large number of scientific publications show the interest in the applications of BN in this field.
Unfortunately, this modeling formalism is not fully accepted in the industry. The questions facing today's engineers are focused on the validity of BN models and the resulting estimates. Indeed, a BN model is not based on a specific semantic in dependability but offers a general formalism for modeling problems under uncertainty.
This book explains the principles of knowledge structuration to ensure a valid BN and DBN model and illustrate the flexibility and efficiency of these representations in dependability, risk analysis and control of multi-state systems and dynamic systems.
Across five chapters, the authors present several modeling methods and industrial applications are referenced for illustration in real industrial contexts.
Pages
146 pages
Collection
n.c
Parution
2016-08-23
Marque
Wiley-ISTE
EAN papier
9781848219922
EAN PDF
9781119347453

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
146
Taille du fichier
4454 Ko
Prix
163,47 €
EAN EPUB
9781119347446

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
146
Taille du fichier
2304 Ko
Prix
163,47 €

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