Overview
- The first book available on the research of human uncertainty
- Covering three different main areas of uncertainty theory: uncertain variable, uncertain set and uncertain process
- Presents applications of uncertainty theory in industrial engineering, automation and finance
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Uncertainty Research (SUR)
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Table of contents (17 chapters)
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Front Matter
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Back Matter
Keywords
About this book
When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case.
In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees.
This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, control, and finance.
Authors and Affiliations
Bibliographic Information
Book Title: Uncertainty Theory
Authors: Baoding Liu
Series Title: Springer Uncertainty Research
DOI: https://doi.org/10.1007/978-3-662-44354-5
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2015
Hardcover ISBN: 978-3-662-44353-8Published: 13 November 2014
Softcover ISBN: 978-3-662-49988-7Published: 10 September 2016
eBook ISBN: 978-3-662-44354-5Published: 03 November 2014
Series ISSN: 2199-3807
Series E-ISSN: 2199-3815
Edition Number: 4
Number of Pages: XVII, 487
Number of Illustrations: 105 b/w illustrations
Topics: Computational Intelligence, Probability Theory and Stochastic Processes, Probability and Statistics in Computer Science, Operations Research/Decision Theory