Description

Book Synopsis

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 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 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

Uncertainty Quantification in Variational

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    A Paperback by Akhtar A. Khan

    £45.99

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      Book details

      Publisher Taylor & Francis
      Imprint Taylor & Francis Ltd
      Published 5/27/2024
      ISBN-13 9781032148496
      978-1032148496
      ISBN-10 1032148497
      Also in:
      Dictionaries, Reference & Language Information theory

      Description

      Book Synopsis

      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 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 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

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