000			03429nam a22005295i 4500
001			978-0-387-46328-5
003			DE-He213
005			20161121231122.0
007			cr nn 008mamaa
008			100301s2007 xxu| s |||| 0|eng d
020			_a9780387463285 _9978-0-387-46328-5
024	7		_a10.1007/978-0-387-46328-5 _2doi
050		4	_aQA312-312.5
072		7	_aPBKL _2bicssc
072		7	_aMAT034000 _2bisacsh
082	0	4	_a515.42 _223
100	1		_aSalicone, Simona. _eauthor.
245	1	0	_aMeasurement Uncertainty _h[electronic resource] : _bAn Approach via the Mathematical Theory of Evidence / _cby Simona Salicone.
264		1	_aBoston, MA : _bSpringer US, _c2007.
300			_aX, 228 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Series in Reliability Engineering, _x1614-7839
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.
650		0	_aMathematics.
650		0	_aMeasure theory.
650		0	_aProbabilities.
650		0	_aPhysical measurements.
650		0	_aMeasurement.
650		0	_aElectronics.
650		0	_aMicroelectronics.
650	1	4	_aMathematics.
650	2	4	_aMeasure and Integration.
650	2	4	_aElectronics and Microelectronics, Instrumentation.
650	2	4	_aMeasurement Science and Instrumentation.
650	2	4	_aProbability Theory and Stochastic Processes.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387306551
830		0	_aSpringer Series in Reliability Engineering, _x1614-7839
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-46328-5
912			_aZDB-2-SMA
950			_aMathematics and Statistics (Springer-11649)
999			_c508870 _d508870