Sentence examples for models were determined using from inspiring English sources

Imperial equations and prediction models were determined using regression analysis and neural networking, respectively.

The hyper-parameters of the ANN and SVM models were determined using a 10-fold cross-validation scheme.

The significance of the parameters obtained in linear and non-linear form from the models were determined using analysis of variance (ANOVA).

The material properties for the core and skin components of these finite element models were determined using the published data and specifications.

Parameters for the Savanna and Woodland biome livestock models were determined using data from (Barnes et al. 2008) and Barnes et al., unpublished work).

From each plot, the model parameters shown in Tables 1 and 2 for exponential, hyperbolic and developed models were determined using the procedure shown in Appendix A. Having substituted the obtained parameters shown in Tables 1 and 2 in exponential, hyperbolic and developed models, the production rate decline curves shown in Figs. 4, 56 and 7 were obtained.

The appropriate architecture of the neural network models was determined using several steps of training and testing of the models.

The optimum architecture of the neural network models was determined using genetic algorithm (GA) as a single objective constrained optimization problem.

Precision and bias of these models was determined using an independent dataset of 60 plots.

Significance in multivariate models was determined using the likelihood ratio test.

Optimal models are determined using the Bayesian Information Criterion.