Computational Intelligence for Big Data Analysis - Frontier Advances and Applications

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.

List of 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.

Summary

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.

Product details

• Assisted by: D. P. Acharjya (Editor), D.P. Acharjya (Editor), Satchidanand Dehuri (Editor), Satchidananda Dehuri (Editor), Sugata Sanyal (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2016
• EAN: 9783319362007
• ISBN: 978-3-31-936200-7
• No. of pages: 267
• Dimensions: 155 mm x 236 mm x 17 mm
• Weight: 466 g
• Illustrations: XX, 267 p. 83 illus., 12 illus. in color.
• Series: Adaptation, Learning, and Optimization; Adaptation, Learning, and Optimization
• Subjects: Natural sciences, medicine, IT, technology > Technology > General, dictionaries; B, Data Mining, Artificial Intelligence, Wissensbasierte Systeme, Expertensysteme, Ontology, engineering, Data Mining and Knowledge Discovery, Computational Intelligence, Expert systems / knowledge-based systems, Semantics, swarm intelligence, neural network, Rough Computing, Near Set, Soft Set, Machine Learning for Big Data