Quantification of Uncertainty: Improving Efficiency and Technology - QUIET selected contributions (Hardcover, 1st ed. 2020)


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.

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Product Description

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.

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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Lecture Notes in Computational Science and Engineering, 137

Release date

August 2020

Availability

Expected to ship within 10 - 15 working days

First published

2020

Editors

, ,

Dimensions

235 x 155mm (L x W)

Format

Hardcover

Pages

282

Edition

1st ed. 2020

ISBN-13

978-3-03-048720-1

Barcode

9783030487201

Categories

LSN

3-03-048720-2



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