An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This second volume focuses on applications in engineering, biomedical engineering, computational physics and computer science.

Model Order Reduction. Volume 2: Snapshot-Based Methods and Algorithms / Peter, Benner; Grivet Talocia, Stefano; Alfio, Quarteroni; Gianluigi, Rozza; Wil, Schilders; Luís Miguel Silveira,. - ELETTRONICO. - 2:(2021), pp. 1-356. [10.1515/9783110671490]

Model Order Reduction. Volume 2: Snapshot-Based Methods and Algorithms

Stefano Grivet-Talocia;
2021

Abstract

An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This second volume focuses on applications in engineering, biomedical engineering, computational physics and computer science.
9783110671490
9783110671407
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2859096