Sentence examples for construct the prediction from inspiring English sources

As the output voltage cannot be represented as a periodical signal, the paper proposes to predict its temporal variation which is then used to construct the prediction of the output voltage.

The data-set in the G2 generation consisted of 2767 records (2567 records for predicted fillet weight and predicted fillet yield, as 200 records were used to construct the prediction equations), while 5640 records (body weight and standard length) were available in the G3 generation.

The radial basis function network (RBFN) is adopted to construct the prediction model.

A subset of the calculated descriptors selected using factor correlation analysis and forward stepwise regression was used to construct the prediction models.

To construct the prediction formula in the second part, TLCD property tests using free vibration and harmonic forced vibration techniques via a shake table are performed and the experimental results thus calibrated are used.

Considering that there are high level noises and outliers mixed in original industrial data, a quantile regression-based echo state network ensemble (QR-ESNE) is modeled to construct the prediction intervals (PIs) of the BFG generation.

This paper proposed the combination of the multi-objective optimization approach and the ensemble simulation technique to determine the optimal perturbations of distribution parameters for constructing the prediction interval of flood quantiles in FFA.

While most previous literature is focused on how to improve the accuracy of point forecast, we consider constructing the prediction interval (PI) for solar power which is more appropriate for its nature of high variability.

The models were derived with the same descriptors and definition of cytotoxicity as the models built when constructing the prediction networks.

To estimate the ratio (frac{P_{text{te}}(x_{text{tr}})}{P_{text{tr}}(x_{text{tr}})}), also called the importance, researchers construct many kinds of forms of formula 2. Sugiyama et al. [11] computed the importance by minimizing the Kullback Leibler divergence between training and test input densities and constructed the prediction model with a series of Gaussian kernel basis functions.

CLPE designed the project, constructed the prediction models and drafted the manuscript.