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F.E. model updating is a technique that is used to identify and correct uncertain modelling parameters that leads to better predictions of the dynamic behavior of a target structure.
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In (7), the distributions and are the model parameters that should be estimated from training data.
They are usually implemented with the model parameters that are extracted offline.
Covariances of model parameters that can be estimated are strongly dependent on the physics.
Model parameters that have some level of uncertainty are probabilistically described.
A procedure is described for calibration of the model parameters that uses information from isothermal experiments.
The model parameters that are necessary are adapted to one single experiment.
The first one is based on learning the model parameters that maximizes the likelihood of the training data.
b s, b f, and b p are model parameters that depend on the video content [33, 34].
Repeat step 2 to obtain the model parameters that would be used to develop the response surface function.
Any model parameters that need to be tuned after the initial evaluation stage further add to the costs.
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