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008			220625s2022 si | s |1|| 0|eng d
020			_a9789811684845
024	7		_a10.1007/978-981-16-8484-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQ342 _b2022 EB
245	0	0	_aComputational Intelligence in Machine Learning : _bSelect Proceedings of ICCIML 2021 _cedited by Amit Kumar, Jacek M. Zurada, Vinit Kumar Gunjan, Raman Balasubramanian
250			_aFirst edition 2022
264		1	_aSingapore _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XIV, 528 páginas) _b294 ilustraciones, 219 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aLecture Notes in Electrical Engineering _x1876-1119 _v834
505	0		_aMachine Learning-based Project Resource Allocation Fitment Analysis System - (ML-PRAFS) -- Electric Theft Detection using Un-supervised Machine Learning Based Matrix Profile and K Means Clustering Technique -- Placement Analysis - A New Approach to Ease the Recruitment Process -- Continuous Assessment Analyzer using Django -- Fuzzy Logic in Battery Energy Storage System (Bess) -- Fault Classification of Cooling Fans using a CNN-based Approach -- Violence Recognition using Convolutional Neural Networks -- Automated Grading of Citrus Suhuiensis Fruit using Deep Learning Method -- The Future of Car Automation Field with Smart Driverless Technologies -- Diagnosis and Medicine Prediction for Covid-19 using Machine Learning Approach -- Automated Guided Vehicle Robot Localization with Sensor Fusion -- Implementation of Industrial Automation Water Distribution System Utilizing PLC: A Laboratory Set-up -- Control of Thin McKibben Muscles in an Antagonistic Pair Configuration -- Defect Severity Classification of Complex Composites using CWT and CNN -- Detection of Mobile Phone Usage While Driving using Computer Vision and Deep Learning -- Industry Revolution 4.0 Knowledge Assessment in Malaysia.
520			_aThe book includes select proceedings of the International Conference on Computational Intelligence in Machine Learning (ICCIML 2021). The book constitutes peer-reviewed papers on machine learning, computational intelligence, the internet of things, and smart city applications emphasizing multi-disciplinary research in artificial intelligence and cyber-physical systems. This book addresses the comprehensive nature of computational intelligence, artificial intelligence, machine learning, and deep learning to emphasize its character in modeling, identification, optimization, prediction, forecasting, and control of future intelligent systems. The book will be useful for researchers, research scholars, and students to formulate their research ideas and find future directions in these areas. It will help the readers to solve a diverse range of problems in industries and their real-world applications.
988			_aSpringer_Robotics_2022
650		7	_2embne _aInteligencia artificial _vCongresos y asambleas _9413115
650		7	_2embne _9166090 _aAprendizaje automático _vCongresos y asambleas
650		7	_2embne _9483083 _aInternet de los objetos _vCongresos y asambleas
700	1		_aKumar, Amit _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _999038
700	1		_aZurada, Jacek M. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _9682065
700	1		_aGunjan, Vinit Kumar _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt _9681560
700	1		_aBalasubramanian, Raman _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9789811684838
776	0	8	_iPrinted edition: _z9789811684852
776	0	8	_iPrinted edition: _z9789811684869
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-8484-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b06/2022 _dz _eIG _zSI