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The accuracy of this model ranged from 94.4%to97.1%1%.
In 'Validations' section, we validate the accuracy of this model via simulations.
The accuracy of this model is further verified by close correlations with an existing empirical solution.
The accuracy of this model was verified via the experiments, by constructing and testing the prototypes.
However, the accuracy of this model has not been systematically evaluated.
Again, X Y plot was used to verify the accuracy of this model as shown in Fig. 9.
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In order to further examine the accuracy of the model, this paper describes the dynamic validation of the model using field data from a green roof installed on a commercial roof in Chicago.
The accuracy of this global model is discussed and several simulation examples are investigated in order to study the validity of the obtained neural network global model.
The case study in field tests highlights the accuracy of this new model in the interpretation of formation and fracture characteristics compared with conventional uniform-flux fracture model, especially the effective fracture half-length.
The accuracy of this theoretical model was then validated by comparing the prediction with the experimental and numerical results.
The accuracy of this improved model is experimentally tested with the pervaporation of isobutanol water, n-butanol water, an-butanol waterr mixtures on commerciandhydrophilic compositethanol water
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