Synopsis
The need to quantify and characterise uncertainties arising in mathematical models with unknown parameters leads to the rapidly evolving field of uncertainty quantification. This book provides readers with the concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models. It covers concepts from probability and statistics such as parameter selection techniques, frequentist and Bayesian model calibration, propagation of uncertainties, quantification of model discrepancy, and sensitivity analysis. The book goes on to explore applications and open problems from a wide array of disciplines, particularly those such as climate science, hydrology, and nuclear power where uncertainty quantification is crucial for both scientific understanding and public policy. An accompanying web page provides data used in the exercises and other supplementary material. The text is intended as a coursebook for advanced undergraduates and above, and as a resource for researchers in mathematics, statistics, operations research, science, and engineering.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Ralph Smith is a Professor of Mathematics and Associate Director of the Center for Research in Scientific Computation at North Carolina State University.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Uncertainty Quantification: Theory, Implementation, and Applications
Edité par
Society for Industrial & Applied Mathematics,U.S., 2014
ISBN 10 : 161197321X
ISBN 13 : 9781611973211
Neuf
Couverture rigide
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Etat : New. A guide to the quantification of uncertainty in simulation models, aimed at students and researchers in mathematics, science and engineering. Num Pages: 400 pages, Illustrations (black and white). BIC Classification: PBT; PBWH; PDE; TBJ. Category: (P) Professional & Vocational. Dimension: 262 x 182 x 23. Weight in Grams: 898. . 2013. Hardcover. . . . . N° de réf. du vendeur V9781611973211
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Uncertainty Quantification
Edité par
Society for Industrial and Applied Mathematics,U.S., US, 2013
ISBN 10 : 161197321X
ISBN 13 : 9781611973211
Neuf
Couverture rigide
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
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Hardback. Etat : New. The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate implementation of these algorithms. Uncertainty Quantification: Theory, Implementation, and Applications provides readers with the basic concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models arising in a broad range of disciplines.The book begins with a detailed discussion of applications where uncertainty quantification is critical for both scientific understanding and policy. It then covers concepts from probability and statistics, parameter selection techniques, frequentist and Bayesian model calibration, propagation of uncertainties, quantification of model discrepancy, surrogate model construction, and local and global sensitivity analysis. The author maintains a complementary web page where readers can find data used in the exercises and other supplementary material.Uncertainty Quantification: Theory, Implementation, and Applications includes a large number of definitions and examples that use a suite of relatively simple models to illustrate concepts; numerous references to current and open research issues; and exercises that illustrate basic concepts and guide readers through the numerical implementation of algorithms for prototypical problems. It also features a wide range of applications, including weather and climate models, subsurface hydrology and geology models, nuclear power plant design, and models for biological phenomena, along with recent advances and topics that have appeared in the research literature within the last 15 years, including aspects of Bayesian model calibration, surrogate model development, parameter selection techniques, and global sensitivity analysis.Audience: The text is intended for advanced undergraduates, graduate students, and researchers in mathematics, statistics, operations research, computer science, biology, science, and engineering. It can be used as a textbook for one- or two-semester courses on uncertainty quantification or as a resource for researchers in a wide array of disciplines. A basic knowledge of probability, linear algebra, ordinary and partial differential equations, and introductory numerical analysis techniques is assumed. N° de réf. du vendeur LU-9781611973211
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Uncertainty Quantification - Theory, Implementation, and Applications
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ISBN 13 : 9781611973211
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Uncertainty Quantification Theory, Implementation, and Applications
Edité par
Society for Industrial & Applied, 2014
ISBN 10 : 161197321X
ISBN 13 : 9781611973211
Neuf
Couverture rigide
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Uncertainty Quantification: Theory, Implementation, and Applications
Edité par
Society for Industrial & Applied Mathematics,U.S., 2014
ISBN 10 : 161197321X
ISBN 13 : 9781611973211
Neuf
Couverture rigide
Vendeur : Kennys Bookstore, Olney, MD, Etats-Unis
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Etat : New. A guide to the quantification of uncertainty in simulation models, aimed at students and researchers in mathematics, science and engineering. Num Pages: 400 pages, Illustrations (black and white). BIC Classification: PBT; PBWH; PDE; TBJ. Category: (P) Professional & Vocational. Dimension: 262 x 182 x 23. Weight in Grams: 898. . 2013. Hardcover. . . . . Books ship from the US and Ireland. N° de réf. du vendeur V9781611973211
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Uncertainty Quantification
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Society for Industrial & Applied Mathematics, 2014
ISBN 10 : 161197321X
ISBN 13 : 9781611973211
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Uncertainty Quantification: Theory, Implementation, and Applications
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Society for Industrial & Applied Mathematics,U.S., 2014
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ISBN 13 : 9781611973211
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Couverture rigide
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Uncertainty Quantification: Theory, Implementation, and Applications (eng)
Edité par
Society for Industrial and Applied Mathematics, 2014
ISBN 10 : 161197321X
ISBN 13 : 9781611973211
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Couverture rigide
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Uncertainty Quantification
Edité par
Society for Industrial and Applied Mathematics,U.S., US, 2013
ISBN 10 : 161197321X
ISBN 13 : 9781611973211
Neuf
Couverture rigide
Vendeur : Rarewaves.com UK, London, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardback. Etat : New. The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate implementation of these algorithms. Uncertainty Quantification: Theory, Implementation, and Applications provides readers with the basic concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models arising in a broad range of disciplines.The book begins with a detailed discussion of applications where uncertainty quantification is critical for both scientific understanding and policy. It then covers concepts from probability and statistics, parameter selection techniques, frequentist and Bayesian model calibration, propagation of uncertainties, quantification of model discrepancy, surrogate model construction, and local and global sensitivity analysis. The author maintains a complementary web page where readers can find data used in the exercises and other supplementary material.Uncertainty Quantification: Theory, Implementation, and Applications includes a large number of definitions and examples that use a suite of relatively simple models to illustrate concepts; numerous references to current and open research issues; and exercises that illustrate basic concepts and guide readers through the numerical implementation of algorithms for prototypical problems. It also features a wide range of applications, including weather and climate models, subsurface hydrology and geology models, nuclear power plant design, and models for biological phenomena, along with recent advances and topics that have appeared in the research literature within the last 15 years, including aspects of Bayesian model calibration, surrogate model development, parameter selection techniques, and global sensitivity analysis.Audience: The text is intended for advanced undergraduates, graduate students, and researchers in mathematics, statistics, operations research, computer science, biology, science, and engineering. It can be used as a textbook for one- or two-semester courses on uncertainty quantification or as a resource for researchers in a wide array of disciplines. A basic knowledge of probability, linear algebra, ordinary and partial differential equations, and introductory numerical analysis techniques is assumed. N° de réf. du vendeur LU-9781611973211
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