Quantification of Uncertainty: Improving Efficiency and Technology

QUIET selected contributions

282 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

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.

• Reihe: Lecture Notes in Computational Science and Engineering
• Themen: Mathematik und Naturwissenschaften Mathematik Mathematische Analysis, allgemein Numerische Mathematik
• ISBN: 9783030487232
• Sprache: Englisch
• Erscheinungsdatum: 01.08.2021
• Größe: 23.5 x 15.5 cm
• Verlag: Springer International Publishing
• Herausgegeben von: Marta D'Elia, Max Gunzburger, Gianluigi Rozza