000			02936nam a22004335i 4500
999			_c368386 _d368386 _x1
001			368386
003			ES-MaUEC
005			20230102121730.0
006			a||||fo|||| 00| 0
007			cr nn 008mamaa
008			220326s2022 sz | s |||| 0|eng d
020			_a9783030964702
024	7		_a10.1007/978-3-030-96470-2 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.D343 _b2022 EB
100	1		_aChen, Xin W. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9683268
245	1	0	_aNetwork Science Models for Data Analytics Automation : _bTheories and Applications _cby Xin W. Chen
250			_aFirst edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (VI, 122 páginas) _b40 ilustraciones, 21 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aAutomation Collaboration & E-Services _x2193-4738 _v9
505	0		_aNetwork Science Models -- Interdependent Critical Infrastructures -- Public Health -- Smart and Autonomous Power Grid -- Water Distribution Systems -- Transportation Systems.
520			_aThis book explains network science and its applications in data analytics for critical infrastructures, engineered systems, and knowledge acquisition. Each chapter describes step-by-step processes of how network science enables and automates data analytics through examples. The book not only dissects modeling techniques and analytical results but also explores the intrinsic development of these models and analyses. This unique approach bridges the gap between theory and practice and channels' managerial and problem-solving skills. Engineers, researchers, and managers would benefit from the extensive theoretical background and practical examples discussed in this book. Advanced undergraduate students and graduate students in mathematics, statistics, engineering, business, public health, and social science may use this book as a one-semester textbook or a reference book. Readers who are more interested in applications may skip Chapter 1 and peruse through the rest of the book with ease.
988			_aSpringer_Robotics_2022
650		7	_2embne _9162648 _aData mining
650		7	_2embne _aIngeniería _9670301
776	0	8	_iPrinted edition: _z9783030964696
776	0	8	_iPrinted edition: _z9783030964719
776	0	8	_iPrinted edition: _z9783030964726
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-96470-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2022 _dz _eIG _zSI