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.
General
Imprint: |
Springer-Verlag
|
Country of origin: |
Germany |
Series: |
Studies in Computational Intelligence, 300 |
Release date: |
November 2011 |
First published: |
2010 |
Editors: |
Baoding Liu
|
Dimensions: |
235 x 155 x 20mm (L x W x T) |
Format: |
Hardcover
|
Pages: |
350 |
Edition: |
2011 |
ISBN-13: |
978-3-642-13958-1 |
Categories: |
Books >
Science & Mathematics >
Mathematics >
Applied mathematics >
Fuzzy set theory
|
LSN: |
3-642-13958-2 |
Barcode: |
9783642139581 |
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