Uncertainty Quantification and Model Calibration

Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has bee...

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Urunga tuihono:ONIX_20231201_9789535132806_816
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collection Directory of Open Access Books
description Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.
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institution Directory of Open Access Books
language eng
publishDate 2023
publishDateRange 2023
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spelling doab-20.500.12854ir-1297072024-04-14T10:28:15Z Uncertainty Quantification and Model Calibration Peter Hessling, Jan kinetics, molecular dynamics, thermodynamics, fault detection, materials science thema EDItEUR::U Computing and Information Technology::UY Computer science::UYM Computer modelling and simulation Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating. 2023-12-01T16:01:26Z 2023-12-01T16:01:26Z 2017 book ONIX_20231201_9789535132806_816 9789535132806 9789535132790 9789535147541 https://directory.doabooks.org/handle/20.500.12854/129707 eng image/jpeg n/a https://www.intechopen.com/books/5832 https://mts.intechopen.com/storage/books/5832/authors_book/authors_book.pdf IntechOpen IntechOpen 10.5772/65579 10.5772/65579 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 9789535132806 9789535132790 9789535147541 IntechOpen 226 open access
spellingShingle kinetics, molecular dynamics, thermodynamics, fault detection, materials science
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYM Computer modelling and simulation
Uncertainty Quantification and Model Calibration
title Uncertainty Quantification and Model Calibration
title_full Uncertainty Quantification and Model Calibration
title_fullStr Uncertainty Quantification and Model Calibration
title_full_unstemmed Uncertainty Quantification and Model Calibration
title_short Uncertainty Quantification and Model Calibration
title_sort uncertainty quantification and model calibration
topic kinetics, molecular dynamics, thermodynamics, fault detection, materials science
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYM Computer modelling and simulation
topic_facet kinetics, molecular dynamics, thermodynamics, fault detection, materials science
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYM Computer modelling and simulation
url ONIX_20231201_9789535132806_816