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Title: Knowledge typology for imprecise probabilities.

When characterizing the reliability of a complex system there are often gaps in the data available for specific subsystems or other factors influencing total system reliability. At Los Alamos National Laboratory we employ ethnographic methods to elicit expert knowledge when traditional data is scarce. Typically, we elicit expert knowledge in probabilistic terms. This paper will explore how we might approach elicitation if methods other than probability (i.e., Dempster-Shafer, or fuzzy sets) prove more useful for quantifying certain types of expert knowledge. Specifically, we will consider if experts have different types of knowledge that may be better characterized in ways other than standard probability theory.
Authors:
 [1] ;  [2]
  1. (Gregory D.)
  2. (Lauren J.)
Publication Date:
OSTI Identifier:
976105
Report Number(s):
LA-UR-02-1257
TRN: US201009%%542
Resource Type:
Conference
Resource Relation:
Conference: Submitted to: Third International Conference on Mathematical Methods in Reliability, June 2002, Trondheim.
Research Org:
Los Alamos National Laboratory
Sponsoring Org:
DOE
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; LANL; PROBABILITY; RELIABILITY