Measurement Uncertainty : An Approach via the Mathematical Theory of Evidence /
By: Salicone, Simona [author.].
Contributor(s): SpringerLink (Online service).
Material type:
BookSeries: Springer Series in Reliability Engineering: Publisher: Boston, MA : Springer US, 2007.Description: X, 228 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9780387463285.Subject(s): Mathematics | Measure theory | Probabilities | Physical measurements | Measurement | Electronics | Microelectronics | Mathematics | Measure and Integration | Electronics and Microelectronics, Instrumentation | Measurement Science and Instrumentation | Probability Theory and Stochastic ProcessesDDC classification: 515.42 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
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E books
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PK Kelkar Library, IIT Kanpur | Available | EBK9157 |
Uncertainty in Measurement -- Fuzzy Variables and Measurement Uncertainty -- The Theory of Evidence -- Random-Fuzzy Variables -- Construction of Random-Fuzzy Variables -- Fuzzy Operators -- The Mathematics of Random-Fuzzy Variables -- Representation of Random-Fuzzy Variables -- Decision-Making Rules with Random-Fuzzy Variables -- List of Symbols.
The expression of uncertainty in measurement is a challenging aspect for researchers and engineers working in instrumentation and measurement because it involves physical, mathematical and philosophical issues. This problem is intensified by the limitations of the probabilistic approach used by the current standard (GUM). This text is the first to make full use of the mathematical theory of evidence to express the uncertainty in measurements. It gives an overview of the current standard, then pinpoints and constructively resolves its limitations through its unique approach. The text presents various tools for evaluating uncertainty, beginning with the probabilistic approach and concluding with the expression of uncertainty using random-fuzzy variables. The exposition is driven by numerous examples. The book is designed for immediate use and application in research and laboratory work. Prerequisites for students include courses in statistics and measurement science. Apart from a classroom setting, this book can be used by practitioners in a variety of fields (including applied mathematics, applied probability, electrical and computer engineering, and experimental physics), and by such institutions as the IEEE, ISA, and National Institute of Standards and Technology.
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