Optimization of Centrifugal Impeller Using Evolutionary Strategies and Artificial Neural Networks

被引：0

作者：

Meier, Rene ^{[1
]}

Joos, Franz ^{[1
]}

机构：

[1] Univ Fed Armed Forces Hamburg, Helmut Schmidt Univ, Lab Turbo Machinery, D-22043 Hamburg, Germany

来源：

ADVANCES IN DATA ANALYSIS, DATA HANDLING AND BUSINESS INTELLIGENCE | 2010年

关键词：

Artificial neural networks; Centrifugal impeller; Evolutionary strategies; Resilient backpropagation;

D O I：

10.1007/978-3-642-01044-6_65

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to optimize turbo machine components it is necessary to describe the behaviour of multimodal objective functions (OF). Instead very time-consuming evaluations using a three-dimensional Navier-Stokes solver have to be performed to get the characteristics of these OF. In this study an Artificial Neural Network (ANN) is considered to use it as a performance predictor with the view to replace the evaluation of the objective function to speed up the optimization process.

引用

页码：713 / 721

页数：9

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