rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Hesitant Fuzzy Sets Theory
  name:
    name part: Xu, Zeshui.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2014
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 466 p. 34 illus., 13 illus. in color. online resource.
  abstract: This book provides the readers with a thorough and systematic introduction to hesitant fuzzy theory. It presents the most recent research results and advanced methods in the field. These includes: hesitant fuzzy aggregation techniques, hesitant fuzzy preference relations, hesitant fuzzy measures, hesitant fuzzy clustering algorithms and hesitant fuzzy multi-attribute decision making methods. Since its introduction by Torra and Narukawa in 2009, hesitant fuzzy sets have become more and more popular and have been used for a wide range of applications, from decision-making problems to cluster analysis, from medical diagnosis to personnel appraisal and information retrieval. This book offers a comprehensive report on the state-of-the-art in hesitant fuzzy sets theory and applications, aiming at becoming a reference guide for both researchers and practitioners in the area of fuzzy mathematics and other applied research fields (e.g. operations research, information science, management science and engineering) characterized by uncertain ("hesitant") information. Because of its clarity and self contained explanations, the book can also be adopted as a textbook from graduate and advanced undergraduate students.
  table of contents: Hesitant Fuzzy Aggregation Operators and Their Applications -- Distance, Similarity, Correlation, Entropy Measures and Clustering -- Algorithms for Hesitant Fuzzy Information -- Hesitant Preference Relations -- Hesitant Fuzzy MADM Models.
  note: by Zeshui Xu.
  subject:
    topic: Engineering
  subject:
    topic: Operations research
  subject:
    topic: Decision making
  subject:
    topic: Management science
  subject:
    topic: Computational intelligence
  subject:
    topic: Engineering
  subject:
    topic: Computational Intelligence
  subject:
    topic: Operations Research, Management Science
  subject:
    topic: Operation Research/Decision Theory
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Fuzziness and Soft Computing, 314
  identifier: 9783319047119
  identifier: http://dx.doi.org/10.1007/978-3-319-04711-9
  record info:
    record creation date: 140130
    record change date: 20151204171627.0
    record identifier: 978-3-319-04711-9