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Quantification of Uncertainty: Improving Efficiency and Technology: QUIET selected contributions
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Dewey Class
518
Title
Quantification of Uncertainty: Improving Efficiency and Technology : QUIET selected contributions (M) / edited by Marta D'Elia, Max Gunzberger, Gianluigi Rozza
Added Personal Name
D'Elia, Marta
Gunzburger, Max
Rozza, Gianluigi
Publication
Cham : Springer , 2020
Physical Details
xii, 272 pages : ill. ; 24 cm.
Series
Lecture Notes in Computational Science and Engineering
; 137
ISBN
9783030487201
Summary Note
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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Subject References:
Applied mathematics
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Computational mathematics
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Engineering mathematics
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Modeling Computer mathematics
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Numerical Analysis
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Authors:
D'Elia, Marta
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Gunzburger, Max
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Rozza, Gianluigi
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Series:
Lecture Notes in Computational Science and Engineering
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Classification:
518
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0000000044175
519.63 QUA
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