Measuring Uncertainty within the Theory of Evidence

Measuring Uncertainty within the Theory of Evidence

This monograph considers the evaluation and expression of measurement uncertainty within the mathematical framework of the Theory of Evidence. With a new perspective on the metrology science, the text paves the way for innovative applications in a wide range of areas. Building on Simona Salicone...

Full description

Bibliographic Details
Main Authors: Salicone, Simona (Author, http://id.loc.gov/vocabulary/relators/aut), Prioli, Marco (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
Edition:1st ed. 2018.
Series:Springer Series in Measurement Science and Technology,
Subjects:
Probabilities.
Probability Theory and Stochastic Processes.
Online Access:Full Text via HEAL-Link
Table of Contents:
  • 1. Introduction
  • Part I: The background of the Measurement Uncertainty
  • 2. Measurements
  • 3. Mathematical Methods to handle Measurement Uncertainty
  • 4. A first, preliminary example
  • Part II: The mathematical Theory of the Evidence
  • 5. Introduction: probability and belief functions
  • 6. Basic definitions of the Theory of Evidence
  • 7. Particular cases of the Theory of Evidence
  • 8. Operators between possibility distributions
  • 9. The joint possibility distributions
  • 10. The combination of the possibility distributions
  • 11. The comparison of the possibility distributions
  • 12. The Probability-Possibility Transformations
  • Part III: The Fuzzy Set Theory and the Theory of the Evidence
  • 13. A short review of the Fuzzy Set Theory
  • 14. The relationship between the Fuzzy Set Theory and the Theory of Evidence
  • Part IV: Measurement Uncertainty within the mathematical framework of the Theory of the Evidence
  • 15. Introduction: towards an alternative representation of the Measurement Results
  • 16. Random-Fuzzy Variables and Measurement Results
  • 17. The Joint Random-Fuzzy variables
  • 18. The Combination of the Random-Fuzzy Variables
  • 19. The Comparison of the Random-Fuzzy Variables
  • 20. Measurement Uncertainty within Fuzzy Inference Systems
  • Part V: Application examples
  • 21. Phantom Power measurement
  • 22. Characterization of a resistive voltage divider
  • 23. Temperature measurement update
  • 24. The Inverted Pendulum
  • 25. Conclusion
  • References
  • Index.

Similar Items