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024 7 $a10.1007/978-3-319-16598-1
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100   $a20150421d2015      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aComputational Intelligence for Big Data Analysis $eFrontier Advances and Applications /$fedited by D.P. Acharjya, Satchidananda Dehuri, Sugata Sanyal
205   $a1st ed. 2015.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015.
215   $a1 online resource (276 p.)
225 1 $aAdaptation, Learning, and Optimization,$x1867-4534 ;$v19
300   $aDescription based upon print version of record.
311   $a3-319-16597-6 
320   $aIncludes bibliographical references and index.
327   $a?Atrain Distributed System? (ADS) : An Infinitely Scalable Architecture for Processing Big Data of any 4Vs -- ?Atrain Distributed System? (ADS) : An Infinitely Scalable Architecture for Processing Big Data of any 4Vs -- Learning Using Hybrid Intelligence Techniques -- Neutrosophic Sets and its Applications to Decision Making -- An Efficient Grouping Genetic Algorithm for Data Clustering and Big Data Analysis -- Self Organizing Migrating Algorithm with Nelder Mead Crossover and Log-Logisti Mutation for Large Scale Optimization -- A Spectrum of Big Data Applications for Data Analytics -- Fundamentals of Brain Signals and its Medical Application Using Data Analysis Techniques -- BigData: Processing of Data Intensive Applications on Cloud -- Framework for Supporting Heterogenous Clouds using Model Driven Approach -- Cloud based Big Data Analytics:WAN Optimization Techniques and Solutions -- Cloud Based E-Governance Solution: A Case Study.
330   $aThe work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The theoretical advancements are supported with illustrative examples and its applications in handling real life problems. The applications are mostly undertaken from real life situations. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing. An elaborate bibliography is provided at the end of each chapter. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of big data analysis and cloud computing.
410  0$aAdaptation, Learning, and Optimization,$x1867-4534 ;$v19
606   $aComputational intelligence
606   $aData mining
606   $aArtificial intelligence
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
615  0$aComputational intelligence.
615  0$aData mining.
615  0$aArtificial intelligence.
615 14$aComputational Intelligence.
615 24$aData Mining and Knowledge Discovery.
615 24$aArtificial Intelligence.
676   $a620.00151
702   $aAcharjya$b D.P$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aDehuri$b Satchidananda$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aSanyal$b Sugata$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a9910299836203321
996   $aComputational Intelligence for Big Data Analysis$91412401
997   $aUNINA