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Titlebook: Quantification of Uncertainty: Improving Efficiency and Technology; QUIET selected contr Marta D‘Elia,Max Gunzburger,Gianluigi Rozza Book 2

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書目名稱Quantification of Uncertainty: Improving Efficiency and Technology
副標題QUIET selected contr
編輯Marta D‘Elia,Max Gunzburger,Gianluigi Rozza
視頻videohttp://file.papertrans.cn/781/780740/780740.mp4
概述Offers 4 crucial modern topics and their synergistic interaction: model order reduction, efficient solvers, high dimensional approximation and applications.Includes contributions, upon invitation, fro
叢書名稱Lecture Notes in Computational Science and Engineering
圖書封面Titlebook: Quantification of Uncertainty: Improving Efficiency and Technology; QUIET selected contr Marta D‘Elia,Max Gunzburger,Gianluigi Rozza Book 2
描述.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..
出版日期Book 2020
關(guān)鍵詞Uncertainty Quantification; Partial Differential Equations; Reduced Order modelling; Computational Mech
版次1
doihttps://doi.org/10.1007/978-3-030-48721-8
isbn_softcover978-3-030-48723-2
isbn_ebook978-3-030-48721-8Series ISSN 1439-7358 Series E-ISSN 2197-7100
issn_series 1439-7358
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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