03356nam a22004815i 4500 978-0-387-46328-5 DE-He213 20260521091918.0 cr nn 008mamaa 100301s2007 xxu| s |||| 0|eng d 9780387463285 99780387463285 10.1007/978-0-387-46328-5 doi CICY 515.42 23 Salicone, Simona. author. Measurement Uncertainty [recurso electrónico] : An Approach via the Mathematical Theory of Evidence / by Simona Salicone. Boston, MA : Springer US, 2007. X, 228 p. 128 illus. online resource. text txt rdacontent computer c rdamedia recurso en línea cr rdacarrier text file PDF rda Springer Series in Reliability Engineering, 1614-7839 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. MATHEMATICS. DISTRIBUTION (PROBABILITY THEORY). WEIGHTS AND MEASURES. ELECTRONICS. MATHEMATICS. MEASURE AND INTEGRATION. ELECTRONICS AND MICROELECTRONICS, INSTRUMENTATION. MEASUREMENT SCIENCE, INSTRUMENTATION. PROBABILITY THEORY AND STOCHASTIC PROCESSES. SpringerLink (Online service) Springer eBooks Printed edition: 9780387306551 Springer Series in Reliability Engineering, 1614-7839 http://dx.doi.org/10.1007/978-0-387-46328-5 Ver el texto completo en las instalaciones del CICY ddc ER 33638 33638 0 0 ddc 0 0 LE CICY CICY EL 2025-07-10 0 515.42 2025-07-10 08:40:00 2025-07-10 ER