Book Description Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book explores four guiding themes - reduced order modelling, high dimensional problems, efficient algorithms, and applications - by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs. Highlighting the most promising approaches for (near-) future improvements in the way uncertainty quantification problems in the partial differential equation setting are solved, and gathering contributions by leading international experts, the book's content will impact the scientific, engineering, financial, economic, environmental, social, and commercial sectors. 296 pp. Englisch. Seller Inventory # 9783030487232

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Quantification of Uncertainty: Improving Efficiency and Technology

Published by Springer, Berlin|Springer International Publishing|Springer (2021)

ISBN 10: 3030487237 ISBN 13: 9783030487232

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Book Description Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book explores four guiding themes - reduced order modelling, high dimensional problems, efficient algorithms, and applications - by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty qu. Seller Inventory # 485151733

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Quantification of Uncertainty - Improving Efficiency and Technology: Quiet Selected Contributions

D'elia, Marta (Editor)/ Gunzburger, Max (Editor)/ Rozza, Gianluigi (Editor)

Published by Springer Nature (2021)

ISBN 10: 3030487237 ISBN 13: 9783030487232

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Book Description Paperback. Condition: Brand New. 293 pages. 9.25x6.10x0.70 inches. In Stock. Seller Inventory # x-3030487237

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Quantification of Uncertainty: Improving Efficiency and Technology : QUIET selected contributions

Marta D'Elia

Published by Springer International Publishing (2021)

ISBN 10: 3030487237 ISBN 13: 9783030487232

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AHA-BUCH GmbH
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Book Description Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores four guiding themes - reduced order modelling, high dimensional problems, efficient algorithms, and applications - by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs. Highlighting the most promising approaches for (near-) future improvements in the way uncertainty quantification problems in the partial differential equation setting are solved, and gathering contributions by leading international experts, the book's content will impact the scientific, engineering, financial, economic, environmental, social, and commercial sectors. Seller Inventory # 9783030487232

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