Uncertainty Theory [recurso electrónico] : A Branch of Mathematics for Modeling Human Uncertainty / by Baoding Liu.

Por: Liu, Baoding [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: TextoTextoSeries Studies in Computational Intelligence ; 300Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Descripción: XI, 350 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642139598Tema(s): Engineering | Artificial intelligence | Management information systems | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics) | e-Commerce/e-business | Business Information SystemsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q342Recursos en línea: Libro electrónicoTexto
Contenidos:
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.
En: Springer eBooksResumen: 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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Tipo de ítem Biblioteca actual Colección Signatura Copia número Estado Fecha de vencimiento Código de barras
Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos Q342 (Browse shelf(Abre debajo)) 1 No para préstamo 374632-2001

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.

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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