000			03629nam a22004455c 4500
988			_aSpringer_Robotics_2020
999			_c115396 _d115396 _x1
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005			20230110040233.0
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008			190903s2020 gw a o |||| 0|eng d
020			_a9783030285531
024	7		_a10.1007/978-3-030-28553-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9 .N37 _b2020 EB
245	0	0	_aNature-inspired computation in data mining and machine learning _cedited by Xin-She Yang, Xing-Shi He
250			_aFirst edition
264		1	_aCham _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XI, 273 páginas) _b87 ilustraciones, 66 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aStudies in Computational Intelligence _x1860-949X _v855
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aAdaptive Improved Flower Pollination Algorithm for Global Optimization -- Algorithms for Optimization and Machine Learning over Cloud -- Implementation of Machine Learning and Data Mining to Improve Cybersecurity and Limit Vulnerabilities to Cyber Attacks -- Comparative analysis of different classifiers on crisis-related tweets: An elaborate study -- An Improved Extreme Learning Machine Tuning by Flower Pollination Algorithm -- Prospects of Machine and Deep Learning in Analysis of Vital Signs for the Improvement of Healthcare Services.
520	3		_aThis book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.
650		7	_2embne _aData mining _9162648
650		7	_2embne _aAprendizaje automático _9166090
650		7	_2embne _aBioinformática _9160489
700	1		_aYang, Xin-She _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt _997941
700	1		_aHe, Xing-Shi _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783030285524
776	0	8	_iPrinted edition: _z9783030285548
776	0	8	_iPrinted edition: _z9783030285555
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-28553-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_aSI _cm _dz _feng _ggw _h0 _b12/2019 _eel _zSI