Sentence examples for mean trend and from inspiring English sources

In this study, the heterogeneity is considered as two components: a deterministic mean trend and a zero-mean random field.

SSA is used for decomposing the original data into two components: the mean trend and the fluctuation component.

In the first step, the decomposition of the original time series by SSA yields the mean trend and the fluctuation component, as shown in Fig. 1.

The training input for SVR is a synthesis of the mean trend and the fluctuation component, which helps to ensure that these two components are independent and do not interfere with each other, leading to more accurate forecast results.

Thus, the initial time series (varvec{y}) is expressed by varvec{y}=varvec{y}^{(1)}+varvec{y}^{(2)} (10 where (varvec{y}^{(1)}) is the mean trend and (varvec{y}^{(2)}) is the fluctuation component.

An example is given in Fig. 1, where a time series collected from the wind power database of Elia, the Belgian transmission system operator (TSO), is decomposed into the mean trend and the fluctuation component.

For example, edgeR moderates dispersion estimates toward a trended mean, whereas DESeq takes the maximum of the individual dispersion estimates and the dispersion-mean trend, and baySeq uses an empirical Bayes approach assuming a negative binomial distribution of the data.

It is used to classify the mean trend segments and find those that are similar to the forecast mean trend segment.

Both components are reconstructed in a phase space to obtain mean trend segments and fluctuation component segments.

Finally, in order to avoid error accumulation and fixed errors, the training input is the synthesis of the similar mean trend segments and the corresponding fluctuation component segments.

Finally, support vector regression is adopted for prediction, where the training input is the synthesis of the similar mean trend segments and the corresponding fluctuation component segments.