Advances in High-Order Predictive Modeling Methodologies and Illustrative Problems
Continuing the author⁰́₉s 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 ⁰́econd-order best-estimate with reduced uncertainties...
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| Format: | eBook |
| Language: | English |
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Boca Raton, FL :
CRC Press,
[2025]
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| Series: | Advances in Applied Mathematics
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| Online Access: | Connect to the full text of this electronic book |
| Summary: | Continuing the author⁰́₉s 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 ⁰́econd-order best-estimate with reduced uncertainties (2nd-BERRU) predictive modeling (PM).⁰́₊ 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. |
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| Physical Description: | 1 online resource (xiv, 288 pages). |
| ISBN: | 9781003478119 1003478115 9781040193228 1040193226 9781040193204 104019320X |