Benefits of Bayesian Network Models.

Cover -- Title Page -- Copyright -- Contents -- Foreword by J.-F. Aubry -- Foreword by L. Portinale -- Acknowledgments -- Introduction -- I.1. Problem statement -- I.2. Book structure -- PART 1. Bayesian Networks -- 1. Bayesian Networks: a Modeling Formalism for System Dependability -- 1.1. Probabilistic graphical models: BN -- 1.1.1. BN: a formalism to model dependability -- 1.1.2. Inference mechanism -- 1.2. Reliability and joint probability distributions -- 1.2.1. Multi-state system example -- 1.2.2. Joint distribution -- 1.2.3. Reliability computing -- 1.2.4. Factorization -- 1.3. Discussion and conclusion -- 2. Bayesian Network: Modeling Formalism of the Structure Function of Boolean Systems -- 2.1. Introduction -- 2.2. BN models in the Boolean case -- 2.2.1. BN model from cut-sets -- 2.2.2. BN model from tie-sets -- 2.2.3. BN model from a top-down approach -- 2.2.4. BN model of a bowtie -- 2.3. Standard Boolean gates CPT -- 2.4. Non-deterministic CPT -- 2.5. Industrial applications -- 2.6. Conclusion -- 3. Bayesian Network: Modeling Formalism of the Structure Function of Multi-State Systems -- 3.1. Introduction -- 3.2. BN models in the multi-state case -- 3.2.1. BN model of multi-state systems from tie-sets -- 3.2.2. BN model of multi-state systems from cut-sets -- 3.2.3. BN model of multi-state systems from functional and dysfunctional analysis -- 3.3. Non-deterministic CPT -- 3.4. Industrial applications -- 3.5. Conclusion -- PART 2. Dynamic Bayesian Networks -- 4. Dynamic Bayesian Networks: Integrating Environmental and Operating Constraints in Reliability Computation -- 4.1. Introduction -- 4.2. Component modeled by a DBN -- 4.2.1. DBN model of a MC -- 4.2.2. DBN model of non-homogeneous MC -- 4.2.3. Stochastic process with exogenous constraint -- 4.3. Model of a dynamic multi-state system -- 4.4. Discussion on dependent processes.

4.5. Conclusion -- 5. Dynamic Bayesian Networks: Integrating Reliability Computation in the Control System -- 5.1. Introduction -- 5.2. Integrating reliability information into the control -- 5.3. Control integrating reliability modeled by DBN -- 5.3.1. Modeling and controlling an over-actuated system -- 5.3.2. Integrating reliability -- 5.4. Application to a drinking water network -- 5.4.1. DBN modeling -- 5.4.2. Results and discussion -- 5.5. Conclusion -- 5.6. Acknowledgments -- Conclusion -- Modeling the functional consequences of failures from structured knowledge -- Dynamic modeling system reliability based on the reliability of components from the environment -- Synthesis of the control law with the aim of optimizing system reliability based on its sensitivity to actuator failures -- Bibliography -- Index -- Other titles from iSTE in Systems and Industrial Engineering - Robotics -- EULA.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.