Sentence examples for models can influence from inspiring English sources

Different initial values of the small signal models can influence both frequencies and damping ratios of oscillation modes, which lay basis for further damping strategy study.

We found that altering the number of classification states in both the fuzzy logic and probability models can influence which networks are predicted by both models.

The authors concluded that the manufacturing quality of camera models can influence the measurement accuracy [e.g., the higher signal to noise ratio (>50 dB) for the Jai camera compared to that (23 dB) of Canon was evidently related to the higher performance of the Jai camera].

Universities can convene current top female leadership to develop leadership skills, and more importantly, cultivate networks through which role models can influence younger women.

The studies were conducted in different years, and variations in costs and prices of preventive and diagnostic strategies used to calibrate the models can influence the results, as well as variations in the values ​​of GDP per capita may influence the interpretation of these results.

The effectiveness of the SADC model can influence the effective functioning of the AU and the SADC member states' DRM systems and vice versa.

However, the existence of interaction between VF and VT makes it impossible to fit VF and VT separately, and changes in the stiffness parameters and in A1 in the tube model can influence both formants and the glottal source.

Indeed, in light of this set of results, it is interesting that we do not always find this behavior for the LIF model with discrete input kicks, in the case where E + I − 2 E I < 0. This disparity in results for the LIF model points out that details of how synaptic inputs are modeled can influence model dynamics in significant ways.

This sort of modeling can influence their thoughts and actions with regard to their experiences in the dating world, and, when used successfully, can ultimately aid them in the creation of new, more positive beliefs and attitudes.

Local sensitivity analysis shows how the uncertainty of parameters of the model can influence the model output.

Two approximately collinear variables in a logistic regression model can influence their significance levels and may change their association with the outcome variable.