Quantification of Uncertainty: QUIET selected contributions (1st ed. 2020) (Lecture Notes in Computational Science and Engineering #137)
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- Synopsis
- 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.
- Copyright:
- 2020
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783030487218
- Related ISBNs:
- 9783030487201
- Publisher:
- Springer International Publishing
- Date of Addition:
- 09/29/20
- Copyrighted By:
- The Editor
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Computers and Internet, Technology, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
- Edited by:
- Marta D'Elia
- Edited by:
- Max Gunzburger
- Edited by:
- Gianluigi Rozza
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- by Marta D’Elia
- by Max Gunzburger
- by Gianluigi Rozza
- in Nonfiction
- in Computers and Internet
- in Technology
- in Mathematics and Statistics