Uncertainty Theory : A Branch of Mathematics for Modeling Human Uncertainty

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 s...

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मुख्य लेखक: Liu, Baoding, 19..-
अन्य लेखक: Liu, Baoding (संपादक)
स्वरूप: Livre numérique
भाषा:Anglais
प्रकाशित: Berlin, Heidelberg : Springer Berlin Heidelberg [20..].
Cham : Springer Nature
संस्करण:1st ed. 2010.
श्रृंखला:Studies in Computational Intelligence 300
ऑनलाइन पहुंच:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
टिप्पणी: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Uncertainty theory, a branch of mathematics for modeling human uncertainty, Baoding Liu, Berlin, Springer, 2010, 1 vol. (XI-350 p.), Studies in computational intelligence, 978-3-642-13958-1
• Uncertainty Theory, Texte imprimé, 9783642422485
• Uncertainty Theory, Texte imprimé, 9783642139604
• Uncertainty theory, a branch of mathematics for modeling human uncertainty, Baoding Liu, Berlin, Springer, 2010, 1 vol. (XI-350 p.), Studies in computational intelligence, 978-3-642-13958-1
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505 1 |a 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 
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520 |a 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 
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