Weber, PhilippeSimon, Christophe
John Wiley & Sons (Asia) Pte.Ltd (Hoboken, New Jersey, 2016) (eng) English9781119347316 UnknownUnknownMATHEMATICS--PROBABILITY--STATISTICS--GENERAL; Includes bibliographical references and index; 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.
Physical dimension
1 online resource (xxiii, 114 p.)UnknownUnknown
Summary / review / table of contents
Front Matter (Pages: i-xxiii)
Part 1 : Bayesian Networks
CHAPTER 1 Bayesian Networks: a Modeling Formalism for System Dependability (Pages: 1-15)
CHAPTER 2 Bayesian Network: Modeling Formalism of the Structure Function of Boolean Systems (Pages: 17-41)
CHAPTER 3 Bayesian Network: Modeling Formalism of the Structure Function of Multi‐State Systems (Pages: 43-63)
Part 2 : Dynamic Bayesian Networks
CHAPTER 4 Dynamic Bayesian Networks: Integrating Environmental and Operating Constraints in Reliability Computation (Pages: 65-82)
CHAPTER 5 Dynamic Bayesian Networks: Integrating Reliability Computation in the Control System (Pages: 83-96)
Conclusion (Pages: 97-99)
Bibliography (Pages: 101-112)
Index (Pages: 113-114)
Other titles from iSTE in Systems and Industrial Engineering – Robotics (Pages: G1-G8)