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008 150903s2007 xxu| o |||| 0|eng d
020 _a9780387463285
_99780387463285
024 7 _a10.1007/9780387463285
_2doi
035 _avtls000331498
039 9 _a201509030732
_bVLOAD
_c201404121851
_dVLOAD
_c201404091619
_dVLOAD
_c201401311417
_dstaff
_y201401301211
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQA312-312.5
100 1 _aSalicone, Simona.
_eautor
_9304498
245 1 0 _aMeasurement Uncertainty :
_bAn Approach via the Mathematical Theory of Evidence /
_cby Simona Salicone.
264 1 _aBoston, MA :
_bSpringer US,
_c2007.
300 _ax, 228 páginas, 128 ilustraciones
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aSpringer Series in Reliability Engineering,
_x1614-7839
500 _aSpringer eBooks
505 0 _aUncertainty 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.
520 _aThe 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.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780387306551
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-46328-5
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c279910
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