Sentence examples for empirical data for validation from inspiring English sources

Having such an option can be fruitful during a development process of a model, as to acquire empirical data for validation of a model may be more difficult or may take a longer time.

Predicted results of sulfuric acid vapor condensation were compared with empirical data for model validation, and the discrepancy is analyzed in terms of measurement and computation uncertainties.

Our data suggests that for species unrelated to Arabidopsis it would be better to use both introns predicted and empirical data for assay design to maximize validation rate and evaluate genetic diversity.

Here, we are talking about facts, about the importance of new empirical data for our assessment of the contemporary moment.

This generates empirical data for consumers who "today are buried under opinions and advertising slogans," said Paul Griff, the chief executive.

These properties may be derived either from theory (in this case one speaks about internal validation) or from empirical data (external validation).

Future works are aimed, on one hand, at achieving empirical data supporting an empirical validation and subsequent calibration of the group cohesion mechanism and then at further extending the model, for instance for representing the movement of elderly and special groups (like elderly and accompanying person), but also leader/follower schemes.

This is a study of diagnostic associations for two common diagnoses in practice populations in very different health care settings, which has the advantage of empirical data collection and the validation of observations between two independent datasets.

The principal obstacle to the validation of these models against empirical data and their use for prediction purposes is the necessity to know the initial distribution of the model parameters.

Here the authors investigated the views on the validation approaches and they show that empirical data plays an important role in the validation practice in all main areas of sustainability science.

Distribution and dissipation studies linking model outputs with empirical data (i.e., model calibration or validation) are welcome.