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Computer Science and Engineering—Theory and Applications pp 183–196Cite as

Big Data and Computational Intelligence: Background, Trends, Challenges, and Opportunities

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Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 143))

Abstract

The boom of technologies such as social media, mobile devices, internet of things, and so on, has generated enormous amounts of data that represent a tremendous challenge, since they come from different sources, different formats and are being generated in real time at an exponential speed which brings with it new necessities, opportunities, and many challenges both in the technical and analytical area. Some of the prevailing necessities lie on the development of computationally efficient algorithms that can extract value and knowledge from data and can manage the noise within in it. Computational intelligence can be seen as a key alternative to manage inaccuracies and extract value from Big Data, using fuzzy logic techniques for a better representation of the problem. And, if the concept of granular computing is also added, we will have new opportunities to decomposition of a complex data model into smaller, more defined, and meaningful granularity levels, therefore different perspectives could yield more manageable models. In this paper, two related subjects are covered, (1) the fundamentals and concepts of Big Data are described, and (2) an analysis of how computational intelligence techniques could bring benefits to this area is discussed.

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Authors and Affiliations

  1. Facultad de Ciencias Químicas e Ingeniería (FCQI), Universidad Autónoma de Baja California, 22390, Tijuana, Baja California, Mexico

    Sukey Nakasima-López, Mauricio A. Sanchez & Juan R. Castro

Authors
  1. Sukey Nakasima-López
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  2. Mauricio A. Sanchez
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  3. Juan R. Castro
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Corresponding author

Correspondence to Sukey Nakasima-López .

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Editors and Affiliations

  1. Calzada Universidad, Tijuana, Baja California, Mexico

    Mauricio A. Sanchez

  2. Calzada Universidad, Tijuana, Baja California, Mexico

    Leocundo Aguilar

  3. Calzada Universidad, Tijuana, Baja California, Mexico

    Manuel Castañón-Puga

  4. Calzada Universidad, Tijuana, Baja California, Mexico

    Antonio Rodríguez-Díaz

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Nakasima-López, S., Sanchez, M.A., Castro, J.R. (2018). Big Data and Computational Intelligence: Background, Trends, Challenges, and Opportunities. In: Sanchez, M., Aguilar, L., Castañón-Puga, M., Rodríguez-Díaz, A. (eds) Computer Science and Engineering—Theory and Applications. Studies in Systems, Decision and Control, vol 143. Springer, Cham. https://doi.org/10.1007/978-3-319-74060-7_10

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  • DOI: https://doi.org/10.1007/978-3-319-74060-7_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74059-1

  • Online ISBN: 978-3-319-74060-7

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