Reliable Computing

, Volume 9, Issue 6, pp 407–418 | Cite as

Dependable Handling of Uncertainty

  • Daniel Berleant
  • Mei-Peng Cheong
  • Chris Chu
  • Yong Guan
  • Ahmed Kamal
  • Gerald Shedblé
  • Scott Ferson
  • James F. Peters


Uncertainty quantification is an important approach to modeling in the presence of limited information about uncertain quantities. As a result recent years have witnessed a burgeoning body of work in this field. The present paper gives some background, highlights some recent work, and presents some problems and challenges.


Mathematical Modeling Recent Work Computational Mathematic Industrial Mathematic Important Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Daniel Berleant
    • 1
  • Mei-Peng Cheong
    • 1
  • Chris Chu
    • 1
  • Yong Guan
    • 1
  • Ahmed Kamal
    • 1
  • Gerald Shedblé
    • 1
  • Scott Ferson
    • 2
  • James F. Peters
    • 3
  1. 1.Department of Electrical and Computer EngineeringIowa State UniversityAmesUSA
  2. 2.Applied BiomathematicsSetauketUSA
  3. 3.Department of Electrical and Computer EngineeringUniversity of ManitobaWinnipegCanada

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