Sentence examples for use of surrogate modelling from inspiring English sources

This paper presents the use of surrogate modelling to address the computational requirements of high fidelity simulations needed to evaluate alternative designs.

A robust numerical implementation of the model is detailed that makes use of surrogate models to capture the thermodynamics.

The use of surrogate models to approximate computationally expensive simulation models, e.g., large comprehensive finite element models, is widespread.

This paper focuses on the general use of surrogate modeling in the design of civil structures and examines six model types that span a wide range of characteristics.

Closing remarks foster on future perspectives, challenges and shortcomings associated with the use of surrogate models by aircraft industrial aerodynamicists, despite their increased interest among the research communities.

For the engineering optimization problems characterized by high computational cost and multiple local optima, the combination use of surrogate model and meta-heuristic algorithm is increasingly popular.

The primary focus here is the application of the methodology to a complex model whose computational expense limits the number of model evaluations to an extent which necessitates the use of surrogate models.

The use of surrogate models to rapidly evaluate design performance can lead to a more in-depth exploration of a design space and reduce computational time of optimization algorithms.

The paper covers the following topics that are deemed important to solve a large optimization problem from a practical viewpoint: (1) hybridized approaches to speed up the convergence rate of EAs; (2) the use of surrogate model to reduce the computational cost stemmed from EAs; (3) reliability based design optimization using EAs; and (4) data mining of Pareto-optimal solutions.

In this concern, the use of surrogate models has been proposed as the alternative to reduce total computation times.

Typical uses of surrogate models include design, optimization, sensitivity analysis and/or uncertainty quantification.