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For a practical application of the updating concept, which is based on the Ensemble Kalman Filter, a simple method for generating prior ensemble members based on block geometries defined in the short-term model and the variogram, is discussed.
The distribution of the error rate among the classes was approximately the same for both methods of generating prior probabilities, although there were slight differences.
Using the network to generate prior probabilities for classification improves the accuracy when compared with generating prior probabilities based on class prevalence.
In the incorrectly classified cases, the difference in posterior probability between the predicted label and the correct label's probability was small (≈ 0.01) for about half the misclassifications and large (≈ 0.4) for the other half; this was also true for both methods of generating prior probabilities.
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In nearly all incorrectly classified cases, the class with the second highest posterior probability was the correct class; although this was true for both methods of generating priors.
Hence, altogether 7 × 120 different FE models are generated prior to simulation.
This is done in order to compare the performance of the updating framework while updating differently generated prior models.
The vanadium borides generate prior to and consequently inhibit the formation of chromium borides during rapid solidification because of lower standard free energy of formation of the former.
This implies that the model predictions can be generated prior to synthesis of these structures and their adsorption affinities can be evaluated entirely in silico.
The primary reason this occurs is because the 10 m DEM was generated prior to the construction of the Pāhoa Marketplace and excavation of the drainage ditch.
The turbulence is generated prior to the simulations and is based on analytic spectral densities of the atmospheric turbulence and a coherence function defining the spatial correlation of the flow.
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