Sentence examples for regression and optimization from inspiring English sources

Based on regression and optimization with software, a new piecewise correlation of Nusselt number is proposed.

The eight-week course begins with an overview of probability and decision analysis — to ensure students understand how uncertainty can be modeled — and then moves into basic statistics, regression, and optimization modeling.

Uniform design method for regression and optimization was proved to be an excellent method to obtain optimum results for multi-level and multi-factor experiments of RP and other process which have a long processing cycle.

Based on the atmospheric radiation database containing 24,862 data points compiled from 7 stations with the elevation from sea level to 2373 m and the reference code MODTRAN, a new atmospheric radiation model is proposed using regression and optimization software.

Based on the analysis of the existing models and the available radiation data, the extensive computer tests of the regression and optimization are conducted, from which the new solar radiation model for direct and diffuse irradiances under clear sky conditions is proposed.

Using the chloride data, regression and optimization analyses were performed to find the parameters for Fick's 2nd Law of diffusion such that they best-fit the experimental data.

Figure 3 Period factors of the mixed-effects diameter increment (A) and survival (B) models developed by using Regression 1, Regression 2 and Optimization approaches.

When the statistics were computed for the fixed-effects models, 'Regression 1' approach turned out to be better than 'Regression 2' approach, and optimization was again clearly better than the other methods (Table 8).

The range analysis, regression analysis and optimization were conducted.

Biomarker concentration levels were standardized using spline-based Cox regression models, and optimization algorithms were used to estimate the weights.

We employ state-of-the-art machine learning tools such as multi-fidelity Gaussian process regression and Bayesian optimization to synthesize data obtained from multi-resolution simulations, and efficiently identify optimal configurations in the design space.