On Modelling Hybrid Uncertainty in Information

Abstract

Numerical induction models are considered in this report to be models that aggregate lower-level information into higher-level measures for decision making. Various forms of uncertainty may be present in such models including hybrid uncertainties within the information elements being aggregated. After a review of some existing approaches for representing higher-order uncertainty in information, a new approach is presented to enable greater fidelity of uncertainty representation, and consequently more rigorous uncertainty management in aggregation operations. Several different applications then demonstrate the proposed procedures which have direct relevance to many Defense decision making models where higher-order uncertainty is ubiquitous. The overall objective of these procedures is to extract as much meaning from the input information as possible.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2007
Accession Number
ADA467752

Entities

People

  • Lewis Warren

Organizations

  • Defence Science and Technology Group

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Command And Control
  • Command And Control Systems
  • Complex Systems
  • Composite Materials
  • Computational Science
  • Computations
  • Data Sets
  • Engineering
  • Fuzzy Sets
  • Operations Research
  • Probability Distributions
  • Random Variables
  • Reliability
  • Set Theory
  • Surveillance
  • Test And Evaluation

Readers

  • Computational Linguistics
  • Computational Modeling and Simulation
  • Distributed Systems and Data Platform Development