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Uncertainty Theory [electronic resource] / by Dr. Baoding Liu.

By: Contributor(s): Material type: TextTextSeries: Studies in Fuzziness and Soft Computing ; 154Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007Description: X, 255 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540731658
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 519 23
LOC classification:
  • TA329-348
  • TA640-643
Online resources:
Contents:
Prerequisites -- Probability Theory -- Credibility Theory -- Chance Theory -- Uncertainty Theory -- Supplements.
In: Springer eBooksSummary: Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, and countable subadditivity axioms. The goal of uncertainty theory is to study the behavior of uncertain phenomena such as fuzziness and randomness. The main topics include probability theory, credibility theory, and chance theory. For this new edition the entire text has been totally rewritten. More importantly, the chapters on chance theory and uncertainty theory are completely new. This book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory. The purpose is to equip the readers with an axiomatic approach to deal with uncertainty. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, industrial engineering, computer science, artificial intelligence, and management science will find this work a stimulating and useful reference.
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E-Book E-Book Central Library Available E-44395

Prerequisites -- Probability Theory -- Credibility Theory -- Chance Theory -- Uncertainty Theory -- Supplements.

Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, and countable subadditivity axioms. The goal of uncertainty theory is to study the behavior of uncertain phenomena such as fuzziness and randomness. The main topics include probability theory, credibility theory, and chance theory. For this new edition the entire text has been totally rewritten. More importantly, the chapters on chance theory and uncertainty theory are completely new. This book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory. The purpose is to equip the readers with an axiomatic approach to deal with uncertainty. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, industrial engineering, computer science, artificial intelligence, and management science will find this work a stimulating and useful reference.

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