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Quantification of Uncertainty: Improving Efficiency and Technology: QUIET selected contributions - Lecture Notes in Computational Science and Engineering 2020 edition
Quantification of Uncertainty: Improving Efficiency and Technology: QUIET selected contributions - Lecture Notes in Computational Science and Engineering
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.
282 pages, 90 Illustrations, color; 23 Illustrations, black and white; XI, 282 p. 113 illus., 90 ill
| メディア | 書籍 Hardcover Book (ハードカバー付きの本) |
| リリース済み | 2020年7月31日 |
| ISBN13 | 9783030487201 |
| 出版社 | Springer Nature Switzerland AG |
| ページ数 | 282 |
| 寸法 | 150 × 220 × 20 mm · 589 g |
| 言語 | ドイツ語 |
| 編集者 | D'Elia, Marta |
| 編集者 | Gunzburger, Max |
| 編集者 | Rozza, Gianluigi |