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

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

Author
Marta D'Elia, Max Gunzburger, Gianluigi Rozza
Publisher
Springer International Publishing;Springer
Language
English
Edition
1st ed.
Year
2020
Page
XI, 282
ISBN
9783030487201,9783030487218
File Type
pdf
File Size
10.4 MiB

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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