A neural-network-based variance decomposition sensitivity analysis
by Francesco Cadini, Enrico Zio, Francesco Di Maio, Vytis Kopustinskas, Rolandas Urbonas
International Journal of Nuclear Knowledge Management (IJNKM), Vol. 2, No. 3, 2007

Abstract: 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.

Online publication date: Sun, 06-May-2007

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Nuclear Knowledge Management (IJNKM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com