| 书目名称 | Quantification of Uncertainty: Improving Efficiency and Technology | | 副标题 | QUIET selected contr | | 编辑 | Marta D‘Elia,Max Gunzburger,Gianluigi Rozza | | 视频video | | | 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 | | 丛书名称 | Lecture Notes in Computational Science and Engineering | | 图书封面 |  | | 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 | | 关键词 | Uncertainty Quantification; Partial Differential Equations; Reduced Order modelling; Computational Mech | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-48721-8 | | isbn_softcover | 978-3-030-48723-2 | | isbn_ebook | 978-3-030-48721-8Series ISSN 1439-7358 Series E-ISSN 2197-7100 | | issn_series | 1439-7358 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
The information of publication is updating
|
|
发表于 2025-3-21 17:53:37
