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Comparison of Granular Computing Models in a Set-Theoretic Framework

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Brain Informatics (BI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7670))

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Abstract

Many granular computing models have been proposed. A set-theoretic framework for constructing granules is easy to understand. A granule is a subset of a universal set, and a granular structure is a family of subsets of the universal set. By comparing set-based granular structures, the relationships and differences among rough set modal, hierarchical multi-dimensional data model and multi-granulation rough set model are discussed in this paper.

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Authors and Affiliations

  1. Department of Computer Science and Technology, Tongji University, Shanghai, 201804, P.R. China

    Ying Wang & Duoqian Miao

Authors
  1. Ying Wang
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  2. Duoqian Miao
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Editor information

Editors and Affiliations

  1. Department of Enterprise Engineering, University of Rome “Tor Vergata”, Viale del Politecnico, 1, 00133, Roma, Italy

    Fabio Massimo Zanzotto

  2. Department of Medical Informatics, Faculty of Medicine, Shimane University, 89-1 Enya-cho, 693-8501, Izumo-city, Shimane, Japan

    Shusaku Tsumoto

  3. Department of Artificial Intelligence, Faculty of Mathematics and Natural Sciences, University of Groningen, Nijenborgh 9, 9747 AG, Groningen, Netherlands

    Niels Taatgen

  4. Department of Computer Science, University of Regina, 3737 Wascana Parkway, S4S 0A2, Regina, SK, Canada

    Yiyu Yao

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© 2012 Springer-Verlag Berlin Heidelberg

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Wang, Y., Miao, D. (2012). Comparison of Granular Computing Models in a Set-Theoretic Framework. In: Zanzotto, F.M., Tsumoto, S., Taatgen, N., Yao, Y. (eds) Brain Informatics. BI 2012. Lecture Notes in Computer Science(), vol 7670. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35139-6_31

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  • DOI: https://doi.org/10.1007/978-3-642-35139-6_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35138-9

  • Online ISBN: 978-3-642-35139-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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