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Comparison between numerical and experimental results show the reliability of the modelling.
Furthermore, the variability among the models was used to evaluate the reliability of the modelling.
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First, a major challenge of parametric methods, like the logistic model, is the robustness and reliability of the modeling.
A comparative analysis between the modelled predictions and experimental results was performed to verify the reliability of the model.
That ran counter to the forecasts of computer climate models, and global warming skeptics have pointed to Antarctica in questioning the reliability of the models.
Reliability of the model is verified by the experiments.
Reliability of the model is verified by bench-scale experiments.
The results validate the reliability of the model.
Sensitivity analysis confirms the reliability of the model.
Coefficient of variation is a measure of the accuracy and reliability of the model.
Plot in this figure has correlation coefficient of 0.951 and indicates the reliability of the model.
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