Uncertainty quantification in variational inequalities: theory, numerics, and applications
Gespeichert in:
| Beteiligte Personen: | , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Boca Raton ; London ; New York
CRC Press
2022
|
| Ausgabe: | First edition |
| Schlagwörter: | |
| Links: | https://doi.org/10.1201/9781315228969 |
| Abstract: | "Uncertainty Quantification (UQ) is an emerging and extremely active research discipline which aims to quantitatively treat any uncertainty in applied models. The primary objective of Uncertainty Quantification in Variational Inequalities: Theory, Numerics, and Applications is to present a comprehensive treatment of uncertainty quantification in variational inequalities and some of its generalizations emerging from various network, economic, and engineering models. Some of the developed techniques also apply to machine learning, neural networks, and related fields. Features First book on uncertainty quantification in variational inequalities emerging from various network, economic, and engineering models. Completely self-contained and lucid in style Aimed for a diverse audience including applied mathematicians, engineers, economists, and professionals from academia Includes the most recent developments on the subject which so far have only been available in the research literature"-- |
| Umfang: | 1 Online-Ressource Illustrationen |
| ISBN: | 9781315228969 1315228963 9781351857659 1351857657 9781351857673 1351857673 9781351857666 1351857665 |
Internformat
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| 520 | 3 | |a "Uncertainty Quantification (UQ) is an emerging and extremely active research discipline which aims to quantitatively treat any uncertainty in applied models. The primary objective of Uncertainty Quantification in Variational Inequalities: Theory, Numerics, and Applications is to present a comprehensive treatment of uncertainty quantification in variational inequalities and some of its generalizations emerging from various network, economic, and engineering models. Some of the developed techniques also apply to machine learning, neural networks, and related fields. Features First book on uncertainty quantification in variational inequalities emerging from various network, economic, and engineering models. Completely self-contained and lucid in style Aimed for a diverse audience including applied mathematicians, engineers, economists, and professionals from academia Includes the most recent developments on the subject which so far have only been available in the research literature"-- | |
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Datensatz im Suchindex
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| author | Gwinner, Joachim 1950- Jadamba, Baasansuren 1971- Khan, Akhtar A. Raciti, Fabio |
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| discipline | Informatik Mathematik |
| edition | First edition |
| format | Electronic eBook |
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| indexdate | 2024-12-20T19:38:07Z |
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| isbn | 9781315228969 1315228963 9781351857659 1351857657 9781351857673 1351857673 9781351857666 1351857665 |
| language | English |
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| publishDate | 2022 |
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| publisher | CRC Press |
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| spellingShingle | Gwinner, Joachim 1950- Jadamba, Baasansuren 1971- Khan, Akhtar A. Raciti, Fabio Uncertainty quantification in variational inequalities theory, numerics, and applications Informationstheorie (DE-588)4026927-9 gnd Variationsungleichung (DE-588)4187420-1 gnd |
| subject_GND | (DE-588)4026927-9 (DE-588)4187420-1 (DE-588)4016928-5 |
| title | Uncertainty quantification in variational inequalities theory, numerics, and applications |
| title_auth | Uncertainty quantification in variational inequalities theory, numerics, and applications |
| title_exact_search | Uncertainty quantification in variational inequalities theory, numerics, and applications |
| title_full | Uncertainty quantification in variational inequalities theory, numerics, and applications Joachim Gwinner (University of the Federal Army Munich, Germany), Baasansuren Jadamba (Rochester Institute of Technology, USA), Akhtar A. Khan (Rochester Institute of Technology, USA), Fabio Raciti (University of Catania, Italy) |
| title_fullStr | Uncertainty quantification in variational inequalities theory, numerics, and applications Joachim Gwinner (University of the Federal Army Munich, Germany), Baasansuren Jadamba (Rochester Institute of Technology, USA), Akhtar A. Khan (Rochester Institute of Technology, USA), Fabio Raciti (University of Catania, Italy) |
| title_full_unstemmed | Uncertainty quantification in variational inequalities theory, numerics, and applications Joachim Gwinner (University of the Federal Army Munich, Germany), Baasansuren Jadamba (Rochester Institute of Technology, USA), Akhtar A. Khan (Rochester Institute of Technology, USA), Fabio Raciti (University of Catania, Italy) |
| title_short | Uncertainty quantification in variational inequalities |
| title_sort | uncertainty quantification in variational inequalities theory numerics and applications |
| title_sub | theory, numerics, and applications |
| topic | Informationstheorie (DE-588)4026927-9 gnd Variationsungleichung (DE-588)4187420-1 gnd |
| topic_facet | Informationstheorie Variationsungleichung Festschrift |
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