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: Reasoning with Rough Sets
    sub title: Logical Approaches to Granularity-Based Framework
  name:
    name part: Akama, Seiki.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Murai, Tetsuya.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Kudo, Yasuo.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2018
    edition: 1st ed. 2018.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 201 p. 12 illus., 7 illus. in color. online resource.
  abstract: This book explores reasoning with rough sets by developing a granularity-based framework. It begins with a brief description of rough set theory. Next, we examine some relations between rough set theory and non-classical logics including modal logic. We also develop a granularity-based framework for reasoning in which various types of reasoning can be formalized. This book will be of interest to researchers working on the areas in Artificial Intelligence, database and logic.
  note: by Seiki Akama, Tetsuya Murai, Yasuo Kudo.
  subject:
    topic: Computational intelligence
  subject:
    topic: Artificial intelligence
  subject:
    topic: Computational Intelligence
  subject:
    topic: Artificial Intelligence
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Intelligent Systems Reference Library, 142
  identifier: 9783319726915
  identifier: https://doi.org/10.1007/978-3-319-72691-5
  record info:
    record creation date: 171230
    record change date: 20191021202836.0
    record identifier: 978-3-319-72691-5