Measuring Uncertainty within the Theory of Evidence is popular PDF and ePub book, written by Simona Salicone in 2018-04-23, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Measuring Uncertainty within the Theory of Evidence can be Read Online from any device for your convenience.
Measuring Uncertainty within the Theory of Evidence Book PDF Summary
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.
Detail Book of Measuring Uncertainty within the Theory of Evidence PDF
- Author : Simona Salicone
- Release : 23 April 2018
- Publisher : Springer
- ISBN : 9783319741390
- Genre : Mathematics
- Total Page : 327 pages
- Language : English
- PDF File Size : 19,6 Mb
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