Book 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.
Table of contents
- Cover
- Title
- Copyright
- Foreword by J.-F. Aubry
- Foreword by L. Portinale
- Acknowledgments
- Introduction
- PART 1: Bayesian Networks
- PART 2: Dynamic Bayesian Networks
- Conclusion
- Bibliography
- Index
- End User License Agreement
Product information
- Title: Benefits of Bayesian Network Models
- Author(s):
- Release date: August 2016
- Publisher(s): Wiley-ISTE
- ISBN: 9781848219922
You might also like
book
Bayesian Networks
Understand the Foundations of Bayesian Networks—Core Properties and Definitions Explained Bayesian Networks: With Examples in R …
book
Introduction to Bayesian Estimation and Copula Models of Dependence
Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods (prior and posterior), Bayes …
book
Probabilistic Reasoning in Intelligent Systems
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and …
book
Probabilistic Deep Learning
Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingly popular probabilistic approach to …