This book focuses on modeling several forms of uncertainty (epistemic and aleatory) and dealing with parameter uncertainty in dependability analysis. For this purpose, we model these forms of uncertainty through additive and non-additive theories. Several theories or modeling languages are used.
After presenting some context on uncertainty sources and several theoretical frameworks for modeling the different forms of uncertainty, the book applies them to the assessment of the performance of system reliability or dependability with usual dependability models. Industrial systems or toy systems are used for the sake of illustration. Beyond the usual models in dependability, the concept of evidential networks is introduced. Similar to Bayesian networks but considering non-additive theories, the modeling principle is explained and applied to several forms of uncertainty and on several systems. This modeling tool is also used to compute importance measures which are necessary to improve systems or test the robustness of the assessment even in the context of several parameter uncertainties.
1. Why and Where Uncertainties.
2. Models and Language of Uncertainty.
3. Risk Graphs and Risk Matrices: Application of Fuzzy Sets and Belief Reasoning.
4. Dependability Assessment Considering Interval-valued Probabilities.
5. Evidential Networks.
6. Reliability Uncertainty and Importance ?Factors.
Christophe Simon is Assistant Professor at the University of Lorraine and is a researcher at the Research Center for Automatic Control of Nancy in France. His research area concerns uncertainty modeling and dependability analysis and prognosis.
Philippe Weber is Full Professor at the University of Lorraine and at the Research Center for Automatic Control of Nancy in France. His interest is focused on probabilistic modeling in maintenance, prognosis and dependability.
Mohamed Sallak is Associate Professor at the University of Technology of Compiègne in France. His current research interests concern dependability assessment of systems under uncertainties.
Table of Contents
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