Study of the Influence of the Initial a Priori Training Dataset Size in the Efficiency and Convergence of Surrogate-Based Evolutionary Optimization

Author:

González-Juarez Daniel,Andrés-Pérez Esther

Publisher

Springer International Publishing

Reference19 articles.

1. Andrés E, Salcedo-Sanz S, Mongue F, Pérez-Bellido A (2012) Efficent aerodynamic design through evolutionary programming and support vector regression algorithms. Expert Syst Appl 39:10700–10708

2. Andrés-Pérez E, Iuliano E (2015) Application of surrogate-based global optimization to aerodynamic design, Springer Tracts in Mechanical Engineering

3. Andrés-Pérez E, González-Juárez D, Martin-Burgos M, Carro-Calvo L, Salcedo-Sanz S (2016) Influence of the number and location of design parameters in the aerodynamic shape optimization of a transonic aerofoil and a wing through evolutionary algorithms and support vector machines. Eng Optim 48

4. Cook P, Mcdoland M, Firmin M (1979) Aerofoil RAE 2822 - Pressure Distributions, and Boundary Layer and Wake Measurements. AGARD Report 138

5. ESDU (1973) Second-order method for estimating the subcritical pressure distribution on a two-dimensional aerofoil in compressible inviscid flow

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