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In the proposed methodology, parameters of hysteretic material models assigned to elements (or substructures) of a nonlinear FE model are updated by minimizing an objective function.
The spine motion assessment was solved into the domain of extended Kalman filters: at each frame of the acquisition, the model pose was updated by minimizing the distances between the measured 2D marker projections on the cameras and the corresponding back-projections of virtual points located on the model surface.
The prediction coefficients are time varying and updated by minimizing the mean square error where (12).
The wave speed model was iteratively updated by minimizing the misfit between the observed and synthetic waveforms.
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Most commonly used ANN for regression problems utilize back propagation (BP) algorithm to update parameters by minimizing the loss between outputs of ANN (hat{y}) and real value y, such as mean square error (MSE).
Specifically, when the ICM algorithm starts, all the pixels of the displacement field are randomly visited and their displacement vectors updated by trying to minimize the potential function (18).
The proposed observer uses longitudinal forces, updates the states by minimizing the longitudinal force estimation error, and provides accurate outcomes at each tire.
The results of the experimental campaign are then used to update the numerical models by minimizing an objective function.
In this perspective, [ 13] use an heuristic in a Boolean framework to update the regulatory structure by minimizing the discrepancies between the reference GRN and a new data set.
Secondly, update u j + 1 by minimizing the differentiable optimization problem in the following: underset{u}{ min}left{{displaystyle sum_{varOmega}left[{leftVert s-{l}^i- urightVert}^2+beta {left[ exp u -0.5right]}^2+lambda {lexp u -0.5right1}-nabla u-{b}_1^jrightVert}^2right]}^2+lambda20).
Secondly, update w j + 1 by minimizing the differentiable optimization problem in the following: underset{w}{ min}left{{displaystyle sum_{varOmega}left[{leftVert s-{r}^{i+1}- wrightVert}^2+gamma {leftVert {t}^{j+1}-nabla w-{b}_2^jrightVert}^2right]}right}, (28).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com