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Approaches to Highly Parameterized Inversion: A Guide to Using PEST for Model-Parameter and Predictive-Uncertainty Analysis

Approaches to Highly Parameterized Inversion: A Guide to Using PEST for Model-Parameter and Predictive-Uncertainty Analysis

Paperback

Technology & Engineering

ISBN10: 1500299987
ISBN13: 9781500299989
Publisher: Createspace
Published: Jun 23 2014
Pages: 78
Weight: 0.45
Height: 0.16 Width: 8.50 Depth: 11.02
Language: English
Analysis of the uncertainty associated with parameters used by a numerical model, and with predictions that depend on those parameters, is fundamental to the use of modeling in support of decisionmaking. Unfortunately, predictive uncer- tainty analysis with regard to models can be very computa- tionally demanding, due in part to complex constraints on parameters that arise from expert knowledge of system proper- ties on the one hand (knowledge constraints) and from the necessity for the model parameters to assume values that allow the model to reproduce historical system behavior on the other hand (calibration constraints).

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