Input parameters of dependability models are often not known accurately. Two principal methods of dealing with such parametric uncertainty are: sensitivity analysis and uncertainty propagation. This paper is an initial attempt to link the two approaches. The case-study used here (i.e., the multi-voltage propulsion system for the Italian High Speed Railway) also enhances the model presented in [6].

Parametric sensitivity and uncertainty propagation in dependability models

PINCIROLI, RICCARDO;
2017

Abstract

Input parameters of dependability models are often not known accurately. Two principal methods of dealing with such parametric uncertainty are: sensitivity analysis and uncertainty propagation. This paper is an initial attempt to link the two approaches. The case-study used here (i.e., the multi-voltage propulsion system for the Italian High Speed Railway) also enhances the model presented in [6].
ValueTools 2016 - 10th EAI International Conference on Performance Evaluation Methodologies and Tools
9781631901416
Epistemic uncertainty propagation; Hierarchical models; Homogeneous and Non-Homogeneous Markov models; Parametric sensitivity analysis; Railway system dependability; Instrumentation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1032031
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