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Advances in High-Order Predictive Modeling

Advances in High-Order Predictive Modeling

Dan Gabriel Cacuci

216,12 €
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Editorial:
Taylor & Francis Ltd
Año de edición:
2024
Materia
Matemáticas
ISBN:
9781032740560

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Continuing the author’s previous work on modeling, this book presents the most recent advances in high-order predictive modeling.

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Otros libros del autor

  • The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I
    Dan Gabriel Cacuci
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  • The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume III
    Dan Gabriel Cacuci
    This text describes a comprehensive adjoint sensitivity analysis methodology (C-ASAM), developed by the author, enabling the efficient and exact computation of arbitrarily high-order functional derivatives of model responses to model parameters in large-scale systems. The model’s responses can be either scalar-valued functionals of the model’s parameters and state variables (as...
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  • The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume III
    Dan Gabriel Cacuci
    This text describes a comprehensive adjoint sensitivity analysis methodology (C-ASAM), developed by the author, enabling the efficient and exact computation of arbitrarily high-order functional derivatives of model responses to model parameters in large-scale systems. The model’s responses can be either scalar-valued functionals of the model’s parameters and state variables (as...
  • The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I
    Dan Gabriel Cacuci
    The computational models of physical systems comprise parameters, independent and dependent variables. Since the physical processes themselves are seldom known precisely and since most of the model parameters stem from experimental procedures which are also subject to imprecisions, the results predicted by these models are also imprecise, being affected by the uncertainties und...
  • BERRU Predictive Modeling
    Dan Gabriel Cacuci
    This book addresses the experimental calibration of best-estimate numerical simulation models. The results of measurements and computations are never exact. Therefore, knowing only the nominal values of experimentally measured or computed quantities is insufficient for applications, particularly since the respective experimental and computed nominal values seldom coincide. In t...