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The model has been tuned using experimental data obtained for a single cell with flow-by design.
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The wear model was tuned using experimental measurements and was then able to accurately predict the volumetric polyethylene wear volume during experiments with different kinematic inputs.
The model parameters were tuned using the experimental data of one gait trial, which resulted in a good fitting accuracy (RMSEs between 0.0491 and 0.1399) between the simulation and experimental synergy activations.
The algorithm parameters are tuned using a 10 replicated 34 experimental design.
The simulated I-V curves were tuned using device parameters to fit the reported experimental data [180].
The model was tuned using gibbsite precipitation data from an extensive experimental program covering a wide range of temperatures, supersaturations, particle sizes, shear rates and solids concentrations relevant to the Bayer process.
Both analytical and SAP2000 outputs are tuned using trail and error method to closely match the experimental output.
Parameters were tuned using only the training data.
Alternative, the controller can be tuned using a single parameter.
Parameters were tuned using 3-fold cross validation.
The hyperparameters were tuned using five-fold cross-validation (CV).
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