Internformat: Nature-inspired algorithms for big data frameworks

Nature-inspired algorithms for big data frameworks:

"This book focuses on application of nature-inspired algorithms for handling issues and challenges posed by big data in diverse environments. It highlights the usability and performance measures of these techniques in dealing with data related problems of emerging areas. It also explore the rol...

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Bibliographische Detailangaben
Weitere Verfasser:	Banati, Hema 1970- (HerausgeberIn), Mehta, Shikha 1977- (HerausgeberIn), Kaur, Parmeet 1976- (HerausgeberIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Hershey, Pennsylvania IGI Global 2018
Schlagworte:	Evolutionary programming (Computer science) Evolutionary computation Computer algorithms Big data
Online-Zugang:	DE-573 DE-1049 DE-91 DE-20 DE-898 DE-706 DE-1050 DE-83 Volltex
Zusammenfassung:	"This book focuses on application of nature-inspired algorithms for handling issues and challenges posed by big data in diverse environments. It highlights the usability and performance measures of these techniques in dealing with data related problems of emerging areas. It also explore the role of machine learning techniques for the optimization and learning involving data intensive applications"--
Beschreibung:	Description based on title screen (IGI Global, viewed 09/07/2018)
Beschreibung:	1 Online-Ressource (28 PDFs (xxii, 412 pages))
ISBN:	9781522558538

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MARC


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Datensatz im Suchindex

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discipline	Informatik
format	Electronic eBook
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isbn	9781522558538
language	English
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spelling	Nature-inspired algorithms for big data frameworks Hema Banati, Shikha Mehta, and Parmeet Kaur, editors Hershey, Pennsylvania IGI Global 2018 1 Online-Ressource (28 PDFs (xxii, 412 pages)) txt rdacontent c rdamedia cr rdacarrier Description based on title screen (IGI Global, viewed 09/07/2018) "This book focuses on application of nature-inspired algorithms for handling issues and challenges posed by big data in diverse environments. It highlights the usability and performance measures of these techniques in dealing with data related problems of emerging areas. It also explore the role of machine learning techniques for the optimization and learning involving data intensive applications"-- Evolutionary programming (Computer science) Evolutionary computation Computer algorithms Big data Banati, Hema 1970- (DE-588)1185996656 edt Mehta, Shikha 1977- (DE-588)1185996990 edt Kaur, Parmeet 1976- (DE-588)1185997407 edt Erscheint auch als Druck-Ausgabe 1522558527 9781522558521 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5852-1 Verlag URL des Erstveröffentlichers Volltex
spellingShingle	Nature-inspired algorithms for big data frameworks Evolutionary programming (Computer science) Evolutionary computation Computer algorithms Big data
title	Nature-inspired algorithms for big data frameworks
title_auth	Nature-inspired algorithms for big data frameworks
title_exact_search	Nature-inspired algorithms for big data frameworks
title_full	Nature-inspired algorithms for big data frameworks Hema Banati, Shikha Mehta, and Parmeet Kaur, editors
title_fullStr	Nature-inspired algorithms for big data frameworks Hema Banati, Shikha Mehta, and Parmeet Kaur, editors
title_full_unstemmed	Nature-inspired algorithms for big data frameworks Hema Banati, Shikha Mehta, and Parmeet Kaur, editors
title_short	Nature-inspired algorithms for big data frameworks
title_sort	nature inspired algorithms for big data frameworks
topic	Evolutionary programming (Computer science) Evolutionary computation Computer algorithms Big data
topic_facet	Evolutionary programming (Computer science) Evolutionary computation Computer algorithms Big data
url	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-5852-1
work_keys_str_mv	AT banatihema natureinspiredalgorithmsforbigdataframeworks AT mehtashikha natureinspiredalgorithmsforbigdataframeworks AT kaurparmeet natureinspiredalgorithmsforbigdataframeworks

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