Efficient Investigation of the Feasible Parameter Set for Large Models
نویسنده
چکیده
In model identification, calibration or sensitivity analysis, the model-parameter values may be required to yield model-output values that satisfy specified constraints, for given initial conditions and forcing. Inequality constraints on scalar functions of the model outputs (henceforth called output bounds) confine the parameters to their feasible set. Output bounds are fundamental to regional sensitivity analysis and a desirable addition to multi-objective calibration.
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