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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Edité par Chapman and Hall/CRC 2019-08-30, 2019
ISBN 10 : 0367379619 ISBN 13 : 9780367379612
Langue: anglais
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Ajouter au panierhardcover. Etat : Good. 1st ed. 2019. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
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Ajouter au panierhardcover. Etat : New. 1st ed. 2019. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Ajouter au panierPaperback. Etat : Brand New. 373 pages. 9.21x6.14x0.79 inches. In Stock.
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Ajouter au panierHardcover. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 1.45.
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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Ajouter au panierHardcover. Etat : new. Hardcover. Continuing the authors previous work on modeling, this book presents the most recent advances in high-order predictive modeling. The author begins with the mathematical framework of the 2nd-BERRU-PM methodology, an acronym that designates the second-order best-estimate with reduced uncertainties (2nd-BERRU) predictive modeling (PM). The 2nd-BERRU-PM methodology is fundamentally anchored in physics-based principles stemming from thermodynamics (maximum entropy principle) and information theory, being formulated in the most inclusive possible phase-space, namely the combined phase-space of computed and measured parameters and responses.The 2nd-BERRU-PM methodology provides second-order output (means and variances) but can incorporate, as input, arbitrarily high-order sensitivities of responses with respect to model parameters, as well as arbitrarily high-order moments of the initial distribution of uncertain model parameters, in order to predict best-estimate mean values for the model responses (i.e., results of interest) and calibrated model parameters, along with reduced predicted variances and covariances for these predicted responses and parameters. Continuing the authors previous work on modeling, this book presents the most recent advances in high-order predictive modeling. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Vendeur : Books Puddle, New York, NY, Etats-Unis
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Ajouter au panierPaperback. Etat : New. New. book.
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Ajouter au panierHardcover. Etat : new. Hardcover. Continuing the authors previous work on modeling, this book presents the most recent advances in high-order predictive modeling. The author begins with the mathematical framework of the 2nd-BERRU-PM methodology, an acronym that designates the second-order best-estimate with reduced uncertainties (2nd-BERRU) predictive modeling (PM). The 2nd-BERRU-PM methodology is fundamentally anchored in physics-based principles stemming from thermodynamics (maximum entropy principle) and information theory, being formulated in the most inclusive possible phase-space, namely the combined phase-space of computed and measured parameters and responses.The 2nd-BERRU-PM methodology provides second-order output (means and variances) but can incorporate, as input, arbitrarily high-order sensitivities of responses with respect to model parameters, as well as arbitrarily high-order moments of the initial distribution of uncertain model parameters, in order to predict best-estimate mean values for the model responses (i.e., results of interest) and calibrated model parameters, along with reduced predicted variances and covariances for these predicted responses and parameters. Continuing the authors previous work on modeling, this book presents the most recent advances in high-order predictive modeling. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
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Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Ajouter au panierHardback. Etat : New. New copy - Usually dispatched within 4 working days. 716.
Vendeur : Majestic Books, Hounslow, Royaume-Uni
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Edité par Springer Nature Switzerland AG, Cham, 2022
ISBN 10 : 3030963632 ISBN 13 : 9783030963637
Langue: anglais
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Ajouter au panierHardcover. Etat : new. Hardcover. 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 underlying the respective model. The functional derivatives (also called sensitivities) of results (also called responses) produced by mathematical/computational models are needed for many purposes, including: (i) understanding the model by ranking the importance of the various model parameters; (ii) performing reduced-order modeling by eliminating unimportant parameters and/or processes; (iii) quantifying the uncertainties induced in a model response due to model parameter uncertainties; (iv) performing model validation, by comparing computations to experiments to address the question does the modelrepresent reality? (v) prioritizing improvements in the model; (vi) performing data assimilation and model calibration as part of forward predictive modeling to obtain best-estimate predicted results with reduced predicted uncertainties; (vii) performing inverse predictive modeling; (viii) designing and optimizing the system.This 3-Volume monograph describes a comprehensive adjoint sensitivity analysis methodology, developed by the author, which enables the efficient and exact computation of arbitrarily high-order sensitivities of model responses in large-scale systems comprising many model parameters. The qualifier comprehensive is employed to highlight that the model parameters considered within the framework of this methodology also include the systems uncertain boundaries and internal interfaces in phase-space. The models responses can be either scalar-valued functionals of the models parameters and state variables (e.g., as customarily encountered in optimization problems) or general function-valued responses. Since linear operators admit bona-fide adjoint operators, responses of models that are linear in the state functions (i.e., dependent variables) can depend simultaneously on both the forward and the adjoint state functions. Hence, the sensitivity analysis of such responses warrants the treatment of linear systems in their own right, rather than treating them as particular cases of nonlinear systems. This is in contradistinction to responses for nonlinear systems, which can depend only on the forward state functions, since nonlinear operators do not admit bona-fide adjoint operators (only a linearized form of a nonlinear operator may admit an adjoint operator). Thus, Volume 1 of this book presents the mathematical framework of the nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as nth-CASAM-L), which is conceived for the most efficient computation of exactly obtained mathematical expressions of arbitrarily-high-order (nth-order) sensitivities of a generic system response with respect to all of the parameters underlying the respective forward/adjoint systems. Volume 2 of this book presents the application of the nth-CASAM-L to perform a fourth-order sensitivity and uncertainty analysis of an OECD/NEA reactor physics benchmark which is representative of a large-scale model comprises many (21,976) uncertain parameters, thereby amply illustrating the unique potential of the nth-CASAM-L to enable the exact and efficient computation of chosen high-order response sensitivities to model parameters. Volume 3 of this book presents the nth-Order Comprehensive Adjoint Sensitivity Analysis Meth Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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