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Uncertainty Quantification in Variational Inequalities Theory, Numerics, and Applications

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   Author: Baturi   |   30 December 2021   |   : 0

English | 2021 | ISBN: 1138626325 | 405 pages | True PDF | 8.46 MB
Uncertainty Quantification (UQ) is an emerging and extremely active research discipline which aims to quantitatively treat any uncertainty in applied models. The primary objective ofUncertainty Quantification in Variational Inequalities: Theory, Numerics, and Applicationsis to present a comprehensive treatment of UQ 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 UQ in variational inequalities emerging from various network, economic, and engineering modelsCompletely self-contained and lucid in styleAimed for a diverse audience including applied mathematicians, engineers, economists, and professionals from academiaIncludes the most recent developments on the subject which so far have only been available in the research literature

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