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The paper proposed a plane constraint calibration method for static error calibration, whilst the dynamic errors are calibrated using a linear inverse dynamic error model.
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The results data have spectral bandwidth of 10 nm and the absolute power error is calibrated to be less than 0.5%.
Imputation error was calibrated by ascertaining the threshold of posterior probability associated with a 10% error rate for the CEU reference panel and a 5% error rate for the YRI reference panel averaged over 6,800 SNPs for which we masked the experimentally determined genotypes.
A parameterized magnetometer measurement error model was established, where the error parameters are calibrated using different calibration algorithms.
The magnitudes of the forecast bias and state error covariances are calibrated by optimizing the innovation statistics of groundwater storage.
PM measured using light-scattering technologies is subject to error because DustTrak photometers are calibrated to aerosols whose characteristics (e.g., shape, size, density, and refractive index) may differ from those in our study and because measured concentration may be affected by factors such as humidity.
In the study, the model parameters are calibrated in order to minimize the prediction errors in a certain building.
VISSIM parameters are calibrated using two different approaches namely trail-and-error approach and genetic algorithm (GA).
The production model parameters,, are calibrated by minimizing the sum of the squared error terms as follows.
Prices are calibrated to City wallets.
If possible, the setpoint i0 of the interaction should be chosen such that the values between i0 - δzrms and i0 + δzrms depend linearly on the tip-sample distance (recall that the error signal is calibrated in length units), where δzrms is the rms roughness of surface morphology.
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