Sentence examples for model extrapolations and from inspiring English sources

Indeed, the carbon-dense areas, e.g. gallery forests and forest patches (e.g. seasonal forest and Cerradão), are associated with the highest standard deviations, as they are model extrapolations and our models will most likely underestimate carbon stocks in these areas.

Finally, uncertainty analysis was done for parameters estimation and model extrapolations.

Although this was a model extrapolation, model and experiment were in good accordance for a wide range of absolute and methanol partial pressures, molar ratios of water to methanol and temperatures.

Furthermore, almost all methods have been focusing on the goodness of fit and the speed of the algorithm, but not necessarily the quality of fit in terms of the validity of the model, extrapolation ability, and predictive power with respect to data not used in the estimation.

A model is regarded valid only within its training domain and only the prediction for new compounds falling within its applicability domain can be considered reliable and not model extrapolations.

A model is considered valid only if it is able to make predictions within its training domain and only the prediction for new compounds falling within its applicability domain can be regarded credible and not model extrapolations.

Model extrapolations, disturbances or sensor faults are first detected through a combined statistic (that considers the calibration region); then, a diagnosis is made by combining statistics pattern recognition, contribution analysis, and disturbance isolation based on historical fault patterns.

It's also an inherently qualitative exercise - there are no questions of percentages or model extrapolations here.

The application then generates a plot showing the whole data, the baseline and threshold values over the training period and model extrapolation for the following year.

Hybrid models take the advantages of both approaches, the mechanistic approach and the empirical/semi-empirical approach, e.g., by improving model extrapolation compared to a pure NN (Van Can et al. 1998) but require complex optimization tools to calibrate them.

4 5 Analyses of 'off-support' data in the presence of structural confounding rely on model extrapolation which do not allow examining the unique contribution of social factors, and thus limit meaningful causal inference.