Sentence examples for in its computations from inspiring English sources

Exact(4)

BWCB gives a much tighter bound than WWCB since it makes use of the channel tap values in its computations.

But the AI can only use historically traced data in its computations, which is then used to anticipate the users' needs and make predictions about the future.

It corrects the R2 value for the sample size and the number of terms in the model by using degrees of freedom in its computations.

FSW conceived of the study, and participated in its computations and coordination.

Similar(56)

Parallel computing is a useful technology for scientific and engineering algorithms/applications. LU-SGS (lower-upper Symmetric-Gauss Seidel method) iSymmetric-Gauss Seidelust schemethod CFD (Computatisnan fluid dynamics) and has strong data defficient in its computandon.

The mean is preferred among the others since it includes all the values in the data set in its computation, minimizing the error in the prediction of any of its values.

For instance, there could be no Turing machine that, when fed with the program number of another machine, would decide whether that machine would eventually come to a halt in its computation or would grind on forever.

The analysis demonstrates that Qe is strongly influenced by the number of flow classes, the fraction of transported sediments and the methodology used in its computation.

The method is based on symmetries of the Fourier transform of the collision integral, where the complexity in its computation is reduced to a separate integral over the unit sphere Sd−1.

Thereupon the taxing officers assessed the tax for that year, and also for 1919, by using in its computation the ratio specified in the last preceding clause of the statute—that is to say, a ratio fixed by contrasting the value of the company's railroad within the state with the value of its entire railroad within and without the state.

To rectify these issues, we modify TFA by including measurement uncertainties in its computation, including ancillary data correlated with noise, and choosing a template set using unsupervised learning approaches such as Agglomerative Hierarchical and KMeans Clustering similar in spirit to a paper by Kim et al. These modifications seem to reduce the variability of lightcurves without over-fitting.

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