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

Contributor(s): Acharjya, D.P [editor.] | Dehuri, Satchidananda [editor.] | Sanyal, Sugata [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Adaptation, Learning, and Optimization: 19Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: XX, 267 p. 83 illus., 12 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319165981.Subject(s): Engineering | Data mining | Artificial intelligence | Computational intelligence | Engineering | Computational Intelligence | Data Mining and Knowledge Discovery | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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.
In: Springer eBooksSummary: 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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"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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