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Information Granules Problem: An Efficient Solution of Real-Time Fuzzy Regression Analysis

  • Azizul Azhar Ramli
  • Junzo WatadaEmail author
  • Witold Pedrycz
Chapter
Part of the Studies in Big Data book series (SBD, volume 8)

Abstract

Currently, Big Data is one of the common scenario which cannot be avoided. The presence of the voluminous amount of unstructured and semi-structured data would take too much time and cost too much money to load into a relational database for analysis purpose. Beside that, regression models are well known and widely used as one of the important categories of models in system modeling. This chapter shows an extended version of fuzzy regression concept in order to handle real-time data analysis of information granules. An ultimate objective of this study is to develop a hybrid of a genetically-guided clustering algorithm called genetic algorithm-based Fuzzy C-Means (GAFCM) and a convex hull-based regression approach, which is regarded as a potential solution to the formation of information granules. It is shown that a setting of Granular Computing with the proposed approach, helps to reduce the computing time, especially in case of real-time data analysis, as well as an overall computational complexity. Additionally, the proposed approach shows an efficient real-time processing of information granules regression analysis based on the convex hull approach in which a Beneath-Beyond algorithm is employed to design sub-convex hulls as well as a main convex hull structure. In the proposed design setting, it was emphasized a pivotal role of the convex hull approach or more specifically the Beneath-Beyond algorithm, which becomes crucial in alleviating limitations of linear programming manifesting in system modeling.

Keywords

Granular computing Fuzzy regression analysis Information granules Fuzzy C-means Convex hulls Convex hull Beneath-beyond algorithm 

Notes

Acknowledgments

The first author was worked with Universiti Tun Hussion Onn Malaysia, MALAYSIA and enrolled as PhD Candidate at Graduate School of Information, Production and Systems (IPS), Waseda University, Fukuoka, JAPAN.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Azizul Azhar Ramli
    • 1
  • Junzo Watada
    • 2
    Email author
  • Witold Pedrycz
    • 3
    • 4
  1. 1.Faculty of Computer Science and Information TechnologyUniversiti Tun Hussein Onn MalaysiaParit Raja, Batu PahatMalaysia
  2. 2.Graduate School of Information, Production and SystemsWaseda UniversityKitakyushu-shiJapan
  3. 3.Department of Electrical and Computer EngineeringUniversity of AlbertaEdmontonCanada
  4. 4.Systems Research InstitutePolish Academy of SciencesWarsawPoland

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