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Computational Intelligence for Big Data Analysis Frontier Advances and Applications / edited by D.P. Acharjya, Satchidananda Dehuri, Sugata Sanyal.

Contributor(s): Acharjya, D.P., editor literario | Dehuri, Satchidananda, editor literario | Sanyal, Sugata., editor literario
Material type: materialTypeLabelE-bookSeries: (Adaptation, Learning, and Optimization,, 1867-4534 ;; 19); (Engineering (Springer-11647)).Publisher: Cham : Springer International Publishing, 2015Description: 1 recurso en línea (XX, 267 páginas 83 ilustraciones, 12 ilustraciones a color.).ISBN: 9783319165981.Subject: Datos masivosOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
"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.
Abstract: The 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.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería Q342 .C667 2015 EB (Browse shelf(Opens below)) Acceso electrónico eBook.12112450
Total holds: 0

"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.

The 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.

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