Benefits of Bayesian Network Models
Language: English
Published by John Wiley & Sons Aug 2016, 2016
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 196.65
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Add to basketItem description from seller
Neuware - 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.
Seller Inventory # 9781848219922
- Title
- Benefits of Bayesian Network Models
- Author
- Christophe Simon
- Publisher
- John Wiley & Sons Aug 2016
- Publication year
- 2016
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 184821992X
- ISBN 13
- 9781848219922
- Item weight
- 237 grams
- Dimensions
- 234x156x8 mm
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.
"Synopsis" may belong to another edition of this title.
About the Author
Christophe Simon is Associate Professor at the Research Centre for Automatic Control in Nancy, France. His research concerns dependability and is mainly focused on modeling engineering and uncertainties.
"About the title" may belong to another edition of this title.
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