000			02986nam a22003495i 4500
001			102374
003			DE-He213
005			20240111050139.0
007			cr nn 008mamaa
008			180503s2018 gw | s |||| 0|eng d
020			_a9783319910260
024	7		_a10.1007/978-3-319-91026-0 _2doi
040			_aES-MaUEC _bspa
050		4	_aQ342 _b2018 EB
100	1		_aPownuk, Andrew _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/5150152932554309830001/
245	1	0	_aCombining Interval, Probabilistic, and Other Types of Uncertainty in Engineering Applications _cby Andrew Pownuk, Vladik Kreinovich.
264		1	_aCham _bSpringer International Publishing _c2018
300			_a1 recurso en línea (XI, 202 páginas 2 ilustraciones, 1 ilustraciones a color)
347			_atext file _bPDF
490	0		_aStudies in Computational Intelligence _x1860-949X _v773
505	0		_aIntroduction -- How to Get More Accurate Estimates -- How to Speed Up Computations -- Towards a Better Understandability of Uncertainty-Estimating Algorithms -- How General Can We Go: What Is Computable and What Is Not -- Decision Making Under Uncertainty -- Conclusions.
520	3		_aHow can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc. In all these developments, the authors' objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty. The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty. .
650		7	_9666321 _aIngeniería asistida por ordenador
650		7	_aInteligencia artificial _2embne _9413115
700	1		_aKreinovich, Vladik _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _0http://id.loc.gov/authorities/names/n95102697 _1http://viaf.org/viaf/37212054/ _998177
776	0	8	_iEdición impresa: _z9783319910253
776	0	8	_iEdición impresa: _z9783319910277
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-91026-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
490	0		_aEngineering (Springer-11647)
988			_aEBSPRINGER_2018
998			_b12/2018 _dz _ea _feng _ggw _h0
999			_c102374 _d102374 _x1