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Advances in High-Order Predictive Modelling

出版	Unknown Publisher, 2024-09
主題	Mathematics / GeneralMathematics / Probability & Statistics / General
ISBN	10327635319781032763538
URL	http://books.google.com.hk/books?id=qtrk0AEACAAJ&hl=&source=gbs_api

註釋"Continuing the author's 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"--