Paper Info
Title
A response-modeling approach to characterization and propagation of uncertainty specified over intervals
Abstract
Computational simulation methods have advanced to a point where simulation can contribute substantially in many areas of systems analysis. One research challenge that has accompanied this transition involves the characterization of uncertainty in both computer model inputs and the resulting system response. This article addresses a subset of the ‘challenge problems’ posed in [Challenge problems: uncertainty in system response given uncertain parameters, 2001] where uncertainty or information is specified over intervals of the input parameters and inferences based on the response are required. The emphasis of the article is to describe and illustrate a method for performing tasks associated with this type of modeling ‘economically’-requiring relatively few evaluations of the system to get a precise estimate of the response. This ‘response-modeling approach’ is used to approximate a probability distribution for the system response. The distribution is then used: (1) to make inferences concerning probabilities associated with response intervals and (2) to guide in determining further, informative, system evaluations to perform.
Year
DOI
Venue
2004
10.1016/j.ress.2004.03.024
Reliability Engineering & System Safety
Keywords
DocType
Volume
Sandia challenge problems,Epistemic uncertainty,Belief functions,Dempster Shafer theory,Interval uncertainty,Computational modeling
Journal
85
Issue
ISSN
Citations 
1
0951-8320
2
PageRank 
References 
Authors
0.43
1
1
Name
Order
Citations
PageRank
Brian Rutherford1628.10