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Computational Intelligence for Big Data Analysis

Frontier Advances and Applications

  • Book
  • © 2015

Overview

Editors:
  1. D.P. Acharjya

    1. School of Computing Sciences and Engineering, VIT University, Vellore, India

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  2. Satchidananda Dehuri

    1. Department of Information and Communication Technology, Fakir Mohan University, Balasore, India

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    You can also search for this editor in PubMed   Google Scholar

  3. Sugata Sanyal

    1. Corporate Technology Office, Tata Consultancy Services, Mumbai, India

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  • Provides recent advances in the fields of big data analysis
  • Emphasizes on theoretical advances and its applications to real life problems
  • Presents theoretical foundations, architecture and tools for big data
  • Treats analytical issues as well as industry and engineering applications

Part of the book series: Adaptation, Learning, and Optimization (ALO, volume 19)

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Table of contents (12 chapters)

  1. Front Matter

    Pages 1-17
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  3. Architecture for Big Data Analysis

    1. Front Matter

      Pages 117-117
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    2. An Efficient Grouping Genetic Algorithm for Data Clustering and Big Data Analysis

      • Sayede Houri Razavi, E. Omid Mahdi Ebadati, Shahrokh Asadi, Harleen Kaur
      Pages 119-142

    3. Self Organizing Migrating Algorithm with Nelder Mead Crossover and Log-Logistic Mutation for Large Scale Optimization

      • Dipti Singh, Seema Agrawal
      Pages 143-164

    4. A Spectrum of Big Data Applications for Data Analytics

      • Ritu Chauhan, Harleen Kaur
      Pages 165-179

    5. Fundamentals of Brain Signals and Its Medical Application Using Data Analysis Techniques

      • P. Geethanjali
      Pages 181-197

  4. Big Data Analysis and Cloud Computing

    1. Front Matter

      Pages 199-199
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    2. BigData: Processing of Data Intensive Applications on Cloud

      • D. H. Manjaiah, B. Santhosh, Jeevan L. J. Pinto
      Pages 201-217

    3. Framework for Supporting Heterogenous Clouds Using Model Driven Approach

      • Aparna Vijaya, V. Neelanarayanan, V. Vijayakumar
      Pages 219-235

    4. Cloud Based Big Data Analytics: WAN Optimization Techniques and Solutions

      • M. Baby Nirmala
      Pages 237-254

    5. Cloud Based E-Governance Solution: A Case Study

      • Monika Mital, Ashis K. Pani, Suma Damodaran
      Pages 255-265

  5. Back Matter

    Pages 267-267
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Keywords

About this book

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.

Editors and Affiliations

  • School of Computing Sciences and Engineering, VIT University, Vellore, India

    D.P. Acharjya

  • Department of Information and Communication Technology, Fakir Mohan University, Balasore, India

    Satchidananda Dehuri

  • Corporate Technology Office, Tata Consultancy Services, Mumbai, India

    Sugata Sanyal

Bibliographic Information

  • Book Title: Computational Intelligence for Big Data Analysis

  • Book Subtitle: Frontier Advances and Applications

  • Editors: D.P. Acharjya, Satchidananda Dehuri, Sugata Sanyal

  • Series Title: Adaptation, Learning, and Optimization

  • DOI: https://doi.org/10.1007/978-3-319-16598-1

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing Switzerland 2015

  • Hardcover ISBN: 978-3-319-16597-4Published: 04 May 2015

  • Softcover ISBN: 978-3-319-36200-7Published: 09 October 2016

  • eBook ISBN: 978-3-319-16598-1Published: 21 April 2015

  • Series ISSN: 1867-4534

  • Series E-ISSN: 1867-4542

  • Edition Number: 1

  • Number of Pages: XX, 267

  • Number of Illustrations: 71 b/w illustrations, 12 illustrations in colour

  • Topics: Computational Intelligence, Data Mining and Knowledge Discovery, Artificial Intelligence

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