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: Uncertainty Theory
    sub title: A Branch of Mathematics for Modeling Human Uncertainty
  name:
    name part: Liu, Baoding.
    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: 2010
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XI, 350 p. online resource.
  abstract: Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, countable subadditivity, and product measure axioms. Uncertainty is any concept that satisfies the axioms of uncertainty theory. Thus uncertainty is neither randomness nor fuzziness. It is also known from some surveys that a lot of phenomena do behave like uncertainty. How do we model uncertainty? How do we use uncertainty theory? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory, including uncertain programming, uncertain risk analysis, uncertain reliability analysis, uncertain process, uncertain calculus, uncertain differential equation, uncertain logic, uncertain entailment, and uncertain inference. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, system science, industrial engineering, computer science, artificial intelligence, finance, control, and management science will find this work a stimulating and useful reference.
  table of contents: Uncertainty Theory -- Uncertain Programming -- Uncertain Risk Analysis -- Uncertain Reliability Analysis -- Uncertain Process -- Uncertain Calculus -- Uncertain Differential Equation -- Uncertain Logic -- Uncertain Entailment -- Uncertain Set Theory -- Uncertain Inference.
  note: by Baoding Liu.
  subject:
    topic: Engineering
  subject:
    topic: Information technology
  subject:
    topic: Business
    topic: Data processing
  subject:
    topic: Artificial intelligence
  subject:
    topic: E-commerce
  subject:
    topic: Computational intelligence
  subject:
    topic: Engineering
  subject:
    topic: Computational Intelligence
  subject:
    topic: Artificial Intelligence (incl. Robotics)
  subject:
    topic: e-Commerce/e-business
  subject:
    topic: IT in Business
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Studies in Computational Intelligence, 300
  identifier: 9783642139598
  identifier: http://dx.doi.org/10.1007/978-3-642-13959-8
  record info:
    record creation date: 100715
    record change date: 20151204142912.0
    record identifier: 978-3-642-13959-8