Sentence examples for gain prediction from inspiring English sources

Application of this formalism to the problem of (i) gain prediction with a given parameters, (ii) gain spectrum engineering for the search of optimum pump power set under the given constraints, (iii) gain clamping problem for the channel reconfiguration, and (iv) derivation of analytic formula for the faster FRA dynamic control have been addressed.

On this basis, acavity receiver heat gain prediction model was establishedbased on a RBF neural network.The simulation results showed that the model predicted values and the measured values had good consistency,so the RBF neural network model could accurately predict the temperature rise of working medium of the solar cavity receiver.

The additional gained prediction power, however, can only be explained by the embedded useful network information that our prediction model automatically learned from real biological network structures.

Predictions of precision optimise the gain of prediction error by facilitating descending predictions (through NMDA receptor activation) and the afferents predicted (through gamma motor neuron drive to intrafusal muscle fibres).

Relative to models based on main effects only, the models that included G×E achieved 9 14% gains in prediction accuracy; adding additive × additive interactions did not increase prediction accuracy consistently across locations.

According to predictive coding implementations of hierarchical Bayesian inference, the gain of prediction error associated with bottom-up signals corresponds to the precision of those prediction errors.

It is necessary to employ weighted factor ω to gain reasonable prediction result because each RBF subnet has different influence on the prediction process.

In general, we only found low to moderate gain in prediction accuracy for both statistical approaches compared to cost-free predictions (i.e., the null model which ignores the person's characteristics and employment history).

Models 2 and 3 produced 'poor' and 'fair' predictions for the presence of lifetime or six month sexual violence, respectively, and only a modest gain in prediction over model 1, which used no human security indicators.

While we did not expect a large gain in prediction reliability, we did expect to see a small gain as has been reported in studies comparing genomic prediction using 50,000 and 777,000 SNPs [ 8– 10].

From this application a negligible gain in prediction accuracy was reached in terms of MAE values (from 13,65 with RVM to 12,62 min with predictions' combination).