View in EDS

An application of fuzzy hypergraphs and hypergraphs in granular computing.

Saved in:
Bibliographic Details
Title: An application of fuzzy hypergraphs and hypergraphs in granular computing.
Authors: Wang, Qian1,2, Gong, Zengtai1 gongzt@nwnu.edu.cn
Source: Information Sciences. Mar2018, Vol. 429, p296-314. 19p.
Subjects: Fuzzy hypergraphs, Granular computing, Data structures, Data mapping, Data encryption
Abstract: Granular computing emphasizes the exploitation of useful structures known as granular structures characterized by multi-level and multi-view. This paper studies the construction of granular structures models using fuzzy hypergraph and hypergraph, so that granules could be represented more intuitively and visually. In fuzzy hypergraph model and hypergraph model of granular computing, a vertex refers to an object, a fuzzy hyperedge or hyperedge corresponds to a granule. In particular, in the hypergraph model, the hyperedge is a partition of the universe, which is got from fuzzy equivalence relation. A fuzzy hypergraph or hypergraph relates to a set of granules and their relations in a specific granularity, and a series of hypergraphs correspond to a hierarchical structure. Based on granular structures, the mapping between fuzzy hypergraphs or hypergraphs presents the relations of the granules in different levels. The results show that it is efficient to represent the partition by means of fuzzy hypergraph and hypergraph, and it is a useful way to represent granular structures through fuzzy hypergraph model or hypergraph model. [ABSTRACT FROM AUTHOR]
Copyright of Information Sciences is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 127076152
AccessLevel: 6
PubType: Periodical
PubTypeId: serialPeriodical
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: An application of fuzzy hypergraphs and hypergraphs in granular computing.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Qian%22">Wang, Qian</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Gong%2C+Zengtai%22">Gong, Zengtai</searchLink><relatesTo>1</relatesTo><i> gongzt@nwnu.edu.cn</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Information+Sciences%22">Information Sciences</searchLink>. Mar2018, Vol. 429, p296-314. 19p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Fuzzy+hypergraphs%22">Fuzzy hypergraphs</searchLink><br /><searchLink fieldCode="DE" term="%22Granular+computing%22">Granular computing</searchLink><br /><searchLink fieldCode="DE" term="%22Data+structures%22">Data structures</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mapping%22">Data mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Data+encryption%22">Data encryption</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Granular computing emphasizes the exploitation of useful structures known as granular structures characterized by multi-level and multi-view. This paper studies the construction of granular structures models using fuzzy hypergraph and hypergraph, so that granules could be represented more intuitively and visually. In fuzzy hypergraph model and hypergraph model of granular computing, a vertex refers to an object, a fuzzy hyperedge or hyperedge corresponds to a granule. In particular, in the hypergraph model, the hyperedge is a partition of the universe, which is got from fuzzy equivalence relation. A fuzzy hypergraph or hypergraph relates to a set of granules and their relations in a specific granularity, and a series of hypergraphs correspond to a hierarchical structure. Based on granular structures, the mapping between fuzzy hypergraphs or hypergraphs presents the relations of the granules in different levels. The results show that it is efficient to represent the partition by means of fuzzy hypergraph and hypergraph, and it is a useful way to represent granular structures through fuzzy hypergraph model or hypergraph model. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Information Sciences is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=127076152
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.ins.2017.11.024
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 19
        StartPage: 296
    Subjects:
      – SubjectFull: Fuzzy hypergraphs
        Type: general
      – SubjectFull: Granular computing
        Type: general
      – SubjectFull: Data structures
        Type: general
      – SubjectFull: Data mapping
        Type: general
      – SubjectFull: Data encryption
        Type: general
    Titles:
      – TitleFull: An application of fuzzy hypergraphs and hypergraphs in granular computing.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Wang, Qian
      – PersonEntity:
          Name:
            NameFull: Gong, Zengtai
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 03
              Text: Mar2018
              Type: published
              Y: 2018
          Identifiers:
            – Type: issn-print
              Value: 00200255
          Numbering:
            – Type: volume
              Value: 429
          Titles:
            – TitleFull: Information Sciences
              Type: main
ResultId 1