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Uncertainty quantification and stochastic modeling with Matlab

Uncertainty Quantification (UQ) is a relatively new research area which describes the methods and approaches used to supply quantitative descriptions of the effects of uncertainty, variability and errors in simulation problems and models. It is rapidly becoming a field of increasing importance, with...

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Detalles Bibliográficos
Autores principales: Souza de Cursi, Eduardo, Sampaio, Rubens
Lenguaje:eng
Publicado: Elsevier Science 2015
Materias:
Acceso en línea:http://cds.cern.ch/record/2121477
Descripción
Sumario:Uncertainty Quantification (UQ) is a relatively new research area which describes the methods and approaches used to supply quantitative descriptions of the effects of uncertainty, variability and errors in simulation problems and models. It is rapidly becoming a field of increasing importance, with many real-world applications within statistics, mathematics, probability and engineering, but also within the natural sciences. Literature on the topic has up until now been largely based on polynomial chaos, which raises difficulties when considering different types of approximation and does no