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, R.;
2017-01-01
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].File in questo prodotto:
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