Use this url to cite publication: https://hdl.handle.net/20.500.12259/278826
A Neural-network-based variance decomposition sensitivity analysis
Type of publication
Straipsnis kitame recenzuojamame leidinyje / Article in other peer-reviewed edition (S5)
Author(s)
| Author | Affiliation | |
|---|---|---|
Cadini, Francesco | ||
Title
A Neural-network-based variance decomposition sensitivity analysis
Is part of
International journal of nuclear knowledge management
Date Issued
| Date | Volume | Issue | Start Page | End Page |
|---|---|---|---|---|
2007 | 2 | 3 | 299 | 312 |
Publisher
Cointrin-Geneva : Inderscience Publishers
Abstract (en)
This paper describes the implementation of an artificial neural network for obtaining the numerous model output calculations within a variance decomposition scheme for performing the model sensitivity analysis with respect to both individual and grouped parameters. A case study concerning the identification of the input variables mostly contributing to model output uncertainty, with reference to an accident scenario in a nuclear power plant, provides evidence of the effectiveness of the approach.
Type of document
text::periodical::journal::contribution to journal::journal article::research article
Language
Anglų / English (en)
Coverage Spatial
Šveicarija / Switzerland (CH)
ISSN (of the container)
1479-540X