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020			_a9783030338206
024	7		_a10.1007/978-3-030-33820-6 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.9.N37 _b2020 EB
245	0	0	_aNature Inspired Computing for Data Science _cedited by Minakhi Rout, Jitendra Kumar Rout, Himansu Das.
250			_a1st ed. 2020.
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2020.
300			_a1 recurso en línea (XII, 295 páginas) _b133 ilustraciones, 98 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 _v871
490	0		_aIntelligent Technologies and Robotics (Springer-42732)
505	0		_aAn Efficient Classification of Tuberous Sclerosis Disease Using Nature Inspired PSO and ACO based Optimized Neural Network -- Mid-term Home Health Care Planning Problem with Flexible Departing Way for Caregivers -- Performance Analysis of NASNet on Unconstrained Ear Recognition -- Optimization of performance parameter for Vehicular Ad-hoc NETwork (VANET) using Swarm Intelligence -- Development of Fast and Reliable Nature-Inspired Computing for Supervised Learning in High-Dimensional Data -- Application of Genetic Algorithms for Unit Commitment and Economic Dispatch Problems in microgrids -- Application of Genetic Algorithms for Designing Micro-Hydro Power Plants in Rural Isolated Areas - a case study in San Miguelito, Honduras -- Performance Evaluation of Different Machine Learning Methods and Deep-Learning Based Convolutional Neural Network for Health Decision Making -- Clustering Bank Customer Complaints on Social Media for Analytical CRM via Multi-Objective Particle Swarm Optimization -- Benchmarking Gene Selection Techniques for Prediction of Distinct Carcinoma from Gene Expression Data: A Computational Study -- An Evolutionary Algorithm based Hybrid Parallel Framework for Asia Foreign Exchange Rate prediction.
520	3		_aThis book discusses the current research and concepts in data science and how these can be addressed using different nature-inspired optimization techniques. Focusing on various data science problems, including classification, clustering, forecasting, and deep learning, it explores how researchers are using nature-inspired optimization techniques to find solutions to these problems in domains such as disease analysis and health care, object recognition, vehicular ad-hoc networking, high-dimensional data analysis, gene expression analysis, microgrids, and deep learning. As such it provides insights and inspiration for researchers to wanting to employ nature-inspired optimization techniques in their own endeavors.
988			_aPrimersemestre_2020_Robotics
650		7	_2embne _aProceso en lenguaje natural (Informática) _9158738
700	1		_aRout, Minakhi. _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aRout, Jitendra Kumar. _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aDas, Himansu. _eeditor _4edt _4http://id.loc.gov/vocabulary/relators/edt
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783030338190
776	0	8	_iPrinted edition: _z9783030338213
776	0	8	_iPrinted edition: _z9783030338220
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-33820-6 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE _n0
998			_b03/2020 _dz _ek _zSI