Quantification of uncertainty [Documento eletrónico] : improving efficiency and technology : QUIET selected contributions / edited by Marta D'Elia, Max Gunzburger, Gianluigi Rozza
Language: eng.Country: Switzerland, Swiss Confederation, Cham.Publication: Cham : Springer International Publishing, 2020Description: XI, 282 p. : il.ISBN: 978-3-030-48721-8.Series: Lecture Notes in Computational Science and Engineering, vol. 137 Subject - Topical Name: Mathematics -- Data processing | Engineering mathematics | Engineering -- Data processing | Computer simulation Online Resources:Click here to access online| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|---|
| E-Books | Biblioteca NOVA FCT Online | Não Ficção | QA71.SPR FCT (Browse shelf(Opens below)) | 1 | Available | 96432 |
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.
There are no comments on this title.
