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001			394157
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008			221011s2022 si | s |||| 0|eng d
020			_a9789811946875
024	7		_a10.1007/978-981-19-4687-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aData, Engineering and Applications _bSelect Proceedings of IDEA 2021 _cedited by Sanjeev Sharma, Sheng-Lung Peng, Jitendra Agrawal, Rajesh K Shukla, Dac-Nhuong Le
250			_a1st edition 2022
264		1	_aSingapore _bSpringer International Publishing _c2022
300			_a1 recurso en línea (IX, 705 páginas) _b314 ilustraciones, 235 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aLecture Notes in Electrical Engineering _x1876-1119 _v907
505	0		_a1. Medical Assistance Chatbot using Deep Learning -- 2. Distortion Controlled Secure Reversible Data Hiding in H.264 videos -- 3. A Method for improving Efficiency and Security of FANET using Chaotic Black Hole Optimization based Routing (BHOR) Technique -- 4. Machine Learning Techniques for Intrusion Detection System: A Survey -- 5. Software Fault Detection by using Rider Optimization Algorithm (ROA) based Deep Neural Network (DNN) -- 6. An Approach for Predicting Admissions in Post Graduate Program by using Machine Learning -- 7. A Survey on Various Representation Learning of Hypergraph for Unsupervised Feature Selection -- 8. A brief study of time series forecasting technique using linear regression, SVM, LSTM, ARIMA and SARIMA -- 9. Adoption of Blockchain Technology for Storage & Verification of Educational Documents -- 10. Obstacle Collision Prediction model for Path Planning Using Obstacle Trajectory Clustering.
520			_aThe book contains select proceedings of the 3rd International Conference on Data, Engineering, and Applications (IDEA 2021). It includes papers from experts in industry and academia that address state-of-the-art research in the areas of big data, data mining, machine learning, data science, and their associated learning systems and applications. This book will be a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of big data applications.
700	1		_aSharma, Sanjeev _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aPeng, Sheng-Lung _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aAgrawal, Jitendra _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aShukla, Rajesh K _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aLe, Dac-Nhuong _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9789811946868
776	0	8	_iPrinted edition: _z9789811946882
776	0	8	_iPrinted edition: _z9789811946899
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-19-4687-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Computer_2022
999			_c394157 _d394157