Modeling and analysis of dependable systems : a probabilistic graphical model perspective / Luigi Portinale and Daniele Codetta Raiteri.
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TextPublication details: Singapore : World Scientific, ©2015.Description: xviii, 251 p. : illustrations ; 24 cmISBN: - 9789814612036
- 000SA.161 23 P852
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 000SA.161 P852 (Browse shelf(Opens below)) | Available | 137049 |
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| 000SA.161 M958 Bayesian nonparametric data analysis / | 000SA.161 N147 Bayesian networks in R : | 000SA.161 P532 Prior processes and their applications : | 000SA.161 P852 Modeling and analysis of dependable systems : | 000SA.161 R569 Approximation methods for efficient learning of Bayesian networks / | 000SA.161 Sa245 Bayesian filtering and smoothing / | 000SA.161 Sc437 Bayesian networks : |
Includes bibliographical references and index.
1. Dependability and Reliability;
2. Probabilistic Graphical Models;
3. From Fault Trees to Bayesian Networks;
4. From Dynamic Fault Tree to Dynamic Bayesian Networks;
5. Decision Theoretic Dependability;
6. The RADyBaN Tool: Supporting Dependability Engineers to Exploit Probabilistic Graphical Models;
7. Case Study 1: Cascading Failures;
8. Case Study 2: Autonomous Fault Detection, Identification and Recovery;
9. Case Study 3: Security Assessment in Critical Infrastructures;
10. Case Study 4: Dynamic Reliability;
Appendix.
The monographic volume addresses, in a systematic and comprehensive way, the state-of-the-art dependability (reliability, availability, risk and safety, security) of systems, using the Artificial Intelligence framework of Probabilistic Graphical Models (PGM). After a survey about the main concepts and methodologies adopted in dependability analysis, the book discusses the main features of PGM formalisms (like Bayesian and Decision Networks) and the advantages, both in terms of modeling and analysis, with respect to classical formalisms and model languages.Methodologies for deriving PGMs from standard dependability formalisms will be introduced, by pointing out tools able to support such a process. Several case studies will be presented and analyzed to support the suitability of the use of PGMs in the study of dependable systems.
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