Parametric Sensitivity and Uncertainty Propagation in Dependability Models

Riccardo Pinciroli; Kishor Trivedi; Andrea Bobbio

10th EAI International Conference on Performance Evaluation Methodologies and Tools

Research Article

Parametric Sensitivity and Uncertainty Propagation in Dependability Models

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/eai.25-10-2016.2266529,
    author={Riccardo Pinciroli and Kishor Trivedi and Andrea Bobbio},
    title={Parametric Sensitivity and Uncertainty Propagation in Dependability Models},
    proceedings={10th EAI International Conference on Performance Evaluation Methodologies and Tools},
    publisher={ACM},
    proceedings_a={VALUETOOLS},
    year={2017},
    month={5},
    keywords={epistemic uncertainty propagation parametric sensitivity analysis homogeneous and non-homogeneous markov models hierarchical models railway system dependability},
    doi={10.4108/eai.25-10-2016.2266529}
}

Riccardo Pinciroli
Kishor Trivedi
Andrea Bobbio
Year: 2017
Parametric Sensitivity and Uncertainty Propagation in Dependability Models
VALUETOOLS
ACM
DOI: 10.4108/eai.25-10-2016.2266529

Riccardo Pinciroli¹^,*, Kishor Trivedi², Andrea Bobbio³

1: Politecnico di Milano
2: Duke University
3: Università del Piemonte Orientale

*Contact email: riccardo.pinciroli@polimi.it

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].

Keywords: epistemic uncertainty propagation parametric sensitivity analysis homogeneous and non-homogeneous markov models hierarchical models railway system dependability

Published: 2017-05-03
Publisher: ACM

: http://dx.doi.org/10.4108/eai.25-10-2016.2266529