Sentence examples for in prediction process from inspiring English sources
The input data is decomposed into three approximated components of (Dh1, Dh2, and Dh3) with lower accuracy together with a more precise component (Ah) which plays the most important role in prediction process [23].
b Plot of average error versus number of attributes to determine optimal number of attributes to use in prediction processes.
From the emergence of AI-driven hedge funds and autonomous financial advisory systems to agricultural predictions based on AI analysis of weather forecasts, AI is supplanting humans in the prediction process in ways that would have been unthinkable a few years ago.
Moreover, some methods use only several tens to hundreds of functional categories in the prediction process which resulted in more generic rather than specific functional assignments.
With the NIPE technique, the rounding operation in the prediction process (that often appears in IPE-based reversible watermarking algorithms to generate integer prediction errors) can be discarded.
We did not use CGI-related features in the prediction process, since most of the ST miRNAs in our dataset do not have primary transcript predictions.
Notably, none of the above methods for predicting multiple locations utilizes inter-dependencies among locations in the prediction process.
In this prediction process, SPRP employs the actual changes of the low-fidelity model response (or the surface approximation model) due to the design variable adjustments.
For this purpose, we are building a parallel wildfire prediction method, which is able to assimilate real-time data to be injected in the prediction process at execution time.
Additionally, this study adopts a moving window approach in the prediction process to deal adequately with the training data set, thereby adapting to the time-varying characteristic of the wind speed.
In this work, variable-updating methods (i.e., update both the model coefficients and effective variables in the prediction process) have been applied to support the robustness of the calibration model when it used to predict heterogeneous samples.
