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Benefits of Bayesian network models
by
Simon, Christophe
, Weber, Philippe
in
Artificial Intelligence
/ Automatic Control Engineering
/ Bayesian statistical decision theory
/ Computer Science
/ Engineering Sciences
/ Mathematical models
/ Uncertainty (Information theory)
2016
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Do you wish to request the book?
Benefits of Bayesian network models
by
Simon, Christophe
, Weber, Philippe
in
Artificial Intelligence
/ Automatic Control Engineering
/ Bayesian statistical decision theory
/ Computer Science
/ Engineering Sciences
/ Mathematical models
/ Uncertainty (Information theory)
2016
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eBook
Benefits of Bayesian network models
2016
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Overview
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.
Publisher
Wiley,ISTE,John Wiley & Sons, Incorporated,Wiley-ISTE,Wiley-Blackwell,ISTE Ltd and John Wiley & Sons Inc
Subject
ISBN
184821992X, 9781848219922
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