Measuring Uncertainty within the Theory of Evidence (Springer Series in Measurement Science and Technology) - Softcover

Buch 9 von 20: Springer Series in Measurement Science and Technology

Salicone, Simona; Prioli, Marco

 
9783030089245: Measuring Uncertainty within the Theory of Evidence (Springer Series in Measurement Science and Technology)
Softcover
ISBN 10: 303008924X ISBN 13: 9783030089245
Verlag: Springer, 2019

Inhaltsangabe

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 tointeract with the proposed approach by generating and combining RFVs through custom measurement functions. With numerous examples of applications, this book provides a comprehensive treatment of the RFV approach to uncertainty that is suitable for any graduate student or researcher with interests in the measurement field. 

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Über die Autorin bzw. den Autor

Simona Salicone is Associate Professor of electrical and electronic measurements in the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano. Her principal research interests are the analysis of advanced mathematical methods for uncertainty representation and estimation, and she has contributed to the development and application of the mathematical Theory of Evidence to the expression and evaluation of uncertainty in measurement. 

Marco Prioli is an IEEE Instrumentation and Measurement Society member. He is also a memeber of the Italian Association for Electrical and Electronic Measurements (GMEE). 

Von der hinteren Coverseite

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 RFVs through custom measurement functions. With numerous examples of applications, this book provides a comprehensive treatment of the RFV approach to uncertainty that is suitable for any graduate student or researcher with interests in the measurement field. 

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Verlag
Springer
Erscheinungsdatum
2019
Sprache
Englisch
ISBN 10 
303008924X
ISBN 13 
9783030089245
Einband
Taschenbuch
Anzahl der Seiten
348
Kontakt zum Hersteller
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9783319741376: Measuring Uncertainty within the Theory of Evidence: Advances within the Theory of Evidence (Springer Series in Measurement Science and Technology)

Vorgestellte Ausgabe

ISBN 10:  3319741373 ISBN 13:  9783319741376
Verlag: Springer, 2018
Hardcover