000 03901nam a22006135i 4500
001 978-981-19-4687-5
003 DE-He213
005 20240423125054.0
007 cr nn 008mamaa
008 221011s2022 si | s |||| 0|eng d
020 _a9789811946875
_9978-981-19-4687-5
024 7 _a10.1007/978-981-19-4687-5
_2doi
050 4 _aTA345-345.5
072 7 _aUN
_2bicssc
072 7 _aCOM018000
_2bisacsh
072 7 _aUN
_2thema
082 0 4 _a620.00285
_223
245 1 0 _aData, Engineering and Applications
_h[electronic resource] :
_bSelect Proceedings of IDEA 2021 /
_cedited by Sanjeev Sharma, Sheng-Lung Peng, Jitendra Agrawal, Rajesh K. Shukla, Dac-Nhuong Le.
250 _a1st ed. 2022.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2022.
300 _aIX, 705 p. 314 illus., 235 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _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.
650 0 _aEngineering
_xData processing.
650 0 _aInformation technology
_xManagement.
650 0 _aMachine learning.
650 0 _aBig data.
650 1 4 _aData Engineering.
650 2 4 _aComputer Application in Administrative Data Processing.
650 2 4 _aMachine Learning.
650 2 4 _aBig Data.
700 1 _aSharma, Sanjeev.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aPeng, Sheng-Lung.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aAgrawal, Jitendra.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aShukla, Rajesh K.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aLe, Dac-Nhuong.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811946868
776 0 8 _iPrinted edition:
_z9789811946882
776 0 8 _iPrinted edition:
_z9789811946899
830 0 _aLecture Notes in Electrical Engineering,
_x1876-1119 ;
_v907
856 4 0 _uhttps://doi.org/10.1007/978-981-19-4687-5
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c173927
_d173927