Measuring Uncertainty within the Theory of Evidence. 1st ed. 2018

種類:

電子ブック

責任表示:

by Simona Salicone, Marco Prioli

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2018

著者名:

• Salicone, Simona.
• Prioli, Marco.
• SpringerLink (Online service)

シリーズ名:

Springer Series in Measurement Science and Technology ;

ISBN:

9783319741390 [331974139X]    

注記:

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 -
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’s Measurement Uncertainty: An Approach via the Mathematical Theory of Evidence, the material covers further developments of the Random Fuzzy Variable (RFV) approach to uncertainty and provides a more robust mathematical and metrological background to the combination of measurement results that leads to a more effective RFV combination method. While the first part of the book introduces measurement uncertainty, the Theory of Evidence, and fuzzy sets, the following parts bring together these concepts and derive an effective methodology for the evaluation and expression of measurement uncertainty. A supplementary downloadable program allows the readers to interact with the proposed approach by generating and combining RF

ローカル注記:

岐阜大学構成員専用E-BOOKS (Gifu University members only)